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  {
   "source": [
    "\n",
    "目前为止，我们已经看到了如何定义网络，计算损失，并更新网络的权重。所以你现在可能会想,\n",
    "\n",
    "数据应该怎么办呢？\n",
    "通常来说，当必须处理图像、文本、音频或视频数据时，可以使用python标准库将数据加载到numpy数组里。然后将这个数组转化成`torch.*Tensor`。\n",
    "\n",
    "对于图片，有 `Pillow`，`OpenCV` 等包可以使用\n",
    "对于音频，有 `scipy` 和 `librosa` 等包可以使用\n",
    "对于文本，不管是原生 python 的或者是基于 Cython 的文本，可以使用 `NLTK` 和 `SpaCy`\n",
    "特别对于视觉方面，我们创建了一个包，名字叫`torchvision`，其中包含了针对`Imagenet`、`CIFAR10`、`MNIST` 等常用数据集的数据加载器 (`data loaders`），还有对图像数据转换的操作，即`torchvision.datasets`和`torch.utils.data.DataLoader`。\n",
    "\n",
    "这提供了极大的便利，可以避免编写样板代码。\n",
    "\n",
    "在这个教程中，我们将使用CIFAR10数据集，它有如下的分类：“飞机”，“汽车”，“鸟”，“猫”，“鹿”，“狗”，“青蛙”，“马”，“船”，“卡车”等。在CIFAR-10里面的图片数据大小是3x32x32，即：三通道彩色图像，图像大小是32x32像素。\n",
    "\n",
    "# 训练一个图片分类器\n",
    "\n",
    "我们将按顺序做以下步骤：\n",
    "\n",
    "1. 通过`torchvision`加载`CIFAR10`里面的训练和测试数据集，并对数据进行标准化\n",
    "2. 定义卷积神经网络\n",
    "3. 定义损失函数\n",
    "4. 利用训练数据训练网络\n",
    "5. 利用测试数据测试网络\n",
    "\n",
    "## 1.加载并标准化CIFAR10\n",
    "使用`torchvision`加载 `CIFAR10` 超级简单。\n",
    "\n",
    "`torchvision` 数据集加载完后的输出是范围在 \\[0, 1\\] 之间的 `PILImage`。我们将其标准化为范围在 \\[-1, 1\\] 之间的张量。"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Files already downloaded and verified\n"
     ]
    }
   ],
   "source": [
    "import torch \n",
    "import torchvision\n",
    "import torchvision.transforms as transforms\n",
    "\n",
    "import os\n",
    "\n",
    "#print('current path :', os.getcwd())\n",
    "\n",
    "transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.5, 0.5, 0.5), (0.5,0.5,0.5))])\n",
    "trainset = torchvision.datasets.CIFAR10(root='.data', train=True, download=False, transform=transform)\n",
    "trainloader = torch.utils.data.DataLoader(trainset, batch_size=4, shuffle=True, num_workers=2)\n",
    "\n",
    "testset = torchvision.datasets.CIFAR10(root='.data', train=False, download=True, transform=transform)\n",
    "testloader = torch.utils.data.DataLoader(testset, batch_size=4, shuffle=False, num_workers=2)\n",
    "\n",
    "classes = ('plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck')  # predfined classes"
   ]
  },
  {
   "source": [
    "乐趣所致，现在让我们可视化部分训练数据。"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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CEFpGztzc3vLhwwdSjHz69JHj6VSZAEPf8+7dA13X1YmgN0TDDAIynr4fWOaZ9apnv9tjjJj7fdex2axZr0Z93BJ4t6a6TzllYohngKor0mtQ3O/3fP78mcPhwFBAX+lJrcukf2uyqI23qlux3+9r/HmeZ4ZhqMHxvu/58OEDOWc+ffpUXTIdhG2w/HA44Jzl6WksHkZfuaRfvjwWS3TNer3GWleBuuv6M4WncbcUXHSgq9u8Wo313O7u7+h8V77/doLtfA/fnvECe7b8GEw2oMmb3Ljy1pzdcTIuJ3IyZCPAV3xj+WwWFzjnTAqBGBeyTjhjyDZhCt+46zu8M2x6jzWwhEiICWMzi4WkJqAxJUFUrqXMR9dmo6MYHsdpIadYFhmNLcqio2wWawzOC/BT5oG1BlwJC6QAORUD4pyRJv/y5I8xVo8n51zDcOv1GqBalrow67hT8AGqu9yGntSibMewhoustdUy1Jh+CIHj8VjjpG2m3FrL7e1ts0Bnbm9vq5elMdgYY+WubjabOtd0Hlhr67m3lqe67dM0XYxrHeeag9B9XG+vwFNdXrUCc1klz25XDfCg8Z9qUb2Kb51di7AEbrdbYkwcjyeWJZwtrizgCRLD6/qel5cdqYKLcNrev3/Pb37z6xLYTez3O5R6tF6t+NWvfmQYBomBXXHN5EG6CiKSpd7hrGE6TZyOJ3JODH1X3IlIG7yP5nzt+nBjjOfM6xubgt48z3UQGmPqd1sQ1Yeqn1M3Wd2f0+lU3XYdYKvVql7jZrOpoKoDRylfGvgXitRcB43eCx3o6qatVitWq1XN8MtgG+rg1tcUPKv1ks+Ww83NlpubmzoATY0/tgnAdtx920wSGCoJkKw/ukg3nypurRhrSgcqMcTWajNXP1C5k2q5ZWPFT7YaLrL03jJ0DmfAZInZR5Pl32UcKPD6xgWnPCN9blOZxEtYyjPizEeOcqyU/RlUs8NmU3idWYCxruepzh05nC4ktpjIb2/CSFhqHF3ZKgpWuqi3vEl91notIQS893WMhhDE+FHPrWGuaNhKx+dms+H29raGstT61Jimjlkdm7ppQlXfU/deQV/njs4B3a/GLdWgUPDs+57T6XTh7ekxr+Ow19ublqc+iG+azIYLRkp7UrpKXDwoBHg67/DOYhhJQ3H7q1uumWQ52WXuGHqPIVfwHIeBzXolD8k7TtYUS7JjtRrYbGTVE0A6J7jgDPDWgEG4m6txFIrJvJQgeM88iQVqXRm4ZeFI/hzzs9ZUS6IuGuoyNdetdJCchVivMZrT6VT/brOC+rnWPdZ9pEKB0Xurr+sgX63kvmiGXvevA+jsCmWMkUIFa6VIQS1TsTQ6+r6rMSEZOOdB9Jbl2YYd9LUff/yBvuvxTgZ3TiUAPy/FQCtg4c6ZfqGZvTUWy+ecx1mNGZuSDYcQCsWnkMPFzS/uvsnyvG1gCVEAPIuzHGO5RynROUNnHL2zjM6eucLGYL3BevAOeiexxcWI92WNYuw5POCswVvhloqrLRl4ksHkjLeGZCzRWVLSmLEYKTmDOjMa6rDG4oxwc8ViPn9IrWljNLRkMNkCVo7xDUteLSu1ykCsNrUQrwnj7ThUUAwhsN/vqwcVQqDrulrgoeAG1IX6w4cPzPPMu3fvuL+/J6XEdru9GD9K4wMYx/GiwEWBrTWM1KDQ4+g8UYOkPY86nsq/9e/2dzvWvxVug2+67devyIDUhVQ+xNmVvTQhLiM85Zc1poAhrMZe0fnCvJYso8UYRwwLq6HHlQmfEtxsVtzf3oiF1Xd4axmHjvVaXM37uy3juKpUK82GglY6FaIuCWfhdrth6Ht2zy8cDwc67zgdD3TeMq4GfNc3sY+EL5PKWYd3hbd3lURpN3Vn1CXx3jPPM7vdroJmjLHSN1JKdeXW/baufUtS1tePx2Ndyfu+5/vvv+fHH3+sQXQFUd1/CAGAZQl1X/r8vnx5rAOqFhzYcxHAdZyonVg60Vpr4ObmFud84SJm5nmqcVc4T+AaszXdmwu2MZbOdWQfq4UWU677DTGWjLtUDolFasmY8u8ZsqaqJIlkrJO4fRR42fSWbnCsO8dt35VMeYnvO0ty4C2MvexlmgsoY+iMqe6+AL3Fews5EzRul6XAwiBJp5wzMTi0lPg8/s9WkwKit1ZodVqmRFkdoMTlJTzVuU7mVRLrfHGOs+90uSn1SCvlNJGqScqWt9kmhPS5aTjo5eXlAjxbz0THglp5apnGGLm9veXm5ubVGAQ4Ho+8vLwA1KRnWzmnoPkWcf160xxBy47RawCqsdW+1hoveq/+TZbnG6dR/zJvvKrJE0HZt/egro2u6LIyq6WqK4VDa8c1DgRtVVE9IJKYMI21phnLsmo352fKCq1WsN78lM+rFdAMZB0kNOdxdRLNhHlrU7O/dcvbIHtrscnuvp1Y0hWx3Y+6XroKg7g1d3d3nE6nOmBbhoAmnRRMW0BtA/cKhi2IXw8qPS+9Fp10ej9r+KHQhVoucBu4b2NR18mE8rBrXNViweZm0c51EW8jSjlrNdFZP8HU94r1lsWdtxa8M/TOyo8vQJuNALAVHqi1xV3OlxxKHRs6rmvMFBk7Wc+rmRvVQnW2JL9kH+rROGvpnMOVv11xwU1OaB5JsvJCdbJ6fDR89ss8zxZ8+r6vSUN9fm9VB7XjWp+7gmG7wF4XmrQL7TAM1UjQ418nmRQoFfgUkK89nvO9/8vb9edbEG0tbH3vLyWL4FuWpz6IZuWRnxKbvzqh12n8t0FFLcFUfrdvV/faqWso9BJjIS2JECJLcVPnZWYuLq9zN2w2W8ZxeAUK5TDllCzG5mJRZJwzrNZr+pjYbLaV/rMsC6dpYr1ZC01HLkdEIq5c4NZlr7/z+d7c3t7y448/cjqd+Pr1ax2gOoDqQ2hiLW28pb2HOqDgPNhijDw9PeG95/b2lq7r+Pu///vK8Xx+fr4AT62p12SBWr/qemmN/eFw4HA41Amgiaw2cN/eaz3HcRxZr9dst1s+fPjADz/8UBMINd5X4rfPz88Alby/Wq3Ybrf1XNotxsTxdCKejngn/MgWHGzJ8UuNoyVlSOV3iLHQmDImiXXnCFgDnZMYZucsd4Nl1XvWneWml4SWsx4MJGuJxhZKkxGjz5RSzRJuyBipHDKlhNkYsEboRUAIkRASBltCR7AZOui9UKYWW8eCtZbNas12vSkx/TJXcgSUU10szwKwpoCsxIVl/+EX5r9ahjquNCz0OhmYvwkkar1eh4Z0/LfAqSCloKjXeb3pZ3Q/bfVRm1H/a7dfMm70PlwbA3/t9rbl2ayOrVv2+gNvGJnNzWtv5LX5L6/RvE9dsW0ZDLqitxSHmFJx18rEtecYBVzSKV4ZMHo+5f/eW5zjIsAdU6zxR+EKUnmLmWaVNO3Fv33D2+xlu6Jfr8htvOaaEqRbW56pAXWlJWnMR3mq33//PfM8M45jLcHTzKi68prIUv6bxl/1OSmZGKjWoT47PbaGJPRcY4y1BFQr0DQzqpNHXbz9fl/HgbryunhdL8aS/JLnIqmQIs6hySckjmtyWXAwIhySJQseUxkMsXFii5HmjaOzMDjL6C2DNwyekuWW39FYorWECHEpdCxjUJEQmth4re7RddUKPSsVT8hoQMEUGpzGTLODTKHWOXrvGb0vte6Nu54lSaRl/c5YXGEwaCFqMz2/ubWWZ5uQeetz189CN/UuvvV+C8KtC/yXNh3Leoy3wO3fAnJ/afuv3de3r8SYmqG8AEJ9m7Oh1Zq+XH/+6vf159pNXX99PUapVdaJrRnnEJYax3PWlbpt/+omG9O4cSldxH7EsJYB25cMu3WWeZoLWEfJeqZEDPEiwSPgqrGsxnV8dQvP/DENoD88PFxUPbRhgr/7u7/j4eGh1qS3gANUkNVz0Ix913UVBHe7HV+/fq2re+tGt/FTTVKdTqcKpF+/fuV0OvGv//qvdRFScGwXAl1Qd7tdTTbo8TSLqq6gUlH0O2qBqoWprpxat7oYtJs1hq6z2GgZvaF3ahnK+JxDJiYIGUK2xPJYbEZjOIDBOIchM/pMbzOr3nG/6ei85X7jGTvH4AxjV45ZjhONJWKZcuak3E5j4WKRM8XNR8ZDWVytLeIipZJIvTrDOdHUdY7eXoLFYMGVKjySaDWIAlM5vsbn7Dm5pcn1oiHFbL4dQqvz7Y3tl8BEjQjaMN31+1du+FvHrF4bBUdKLEKn1DkE92930f8/tb1Jkm9Mz+JelxhABYvm0415f/3aX3OxZ1BN56OX4ypoacnV8XgoAepzltmWOnsRuXh9k68BtL5vLN4Jh7XvB1YrqXY4TSeWMBNjqBZXCIElBJZlZp4nQlguyPs1CHU1FluXRblyHz58qGChlp1acioCstlsKnjq++3nlPCuAKzgmVLi6emJz58/03UdDw8P9H3PZrNhtVpd3Bvd1zRNHI9H5nnm06dPVYJQk1paVaIKT20ctwVYBcabmxvu7++rK9iq82jiLKVUQwpAdevX63VdUC7uo4XeW1JvWXnD6CTL7J1MxslkYoQ5w5RsybRnbMooq91kiwWsydwOmXWX2YyO9zc9nbdsR0/XOToDnZVYeufFxQ7ZEkumfEcQS9dajKMoIMnjR1lDRr0VigsvYZ9cwg22rLfeGBEEMQ7TuTIPZCz1FrpcnrtS5krQVueIjK3yY0wNB9gC8Ke/QqTlGtz+qjkLkiCTL3xzH20+xFwlhYwxdQFQMG53o3mG/18DzHb7RZ7nW26vgRr4fsuabLe3Xn/7ZjQr1VU1hu5HJ+I0nQjhzI0Ut/cMRNfHFLy/1PxTq7SNzYrmY2JZZkIwhHCWuooxXLi/rdSVfuatrU2QwNnN0WB53/cVDDXmpLzPNoak5WZKJlaqU3utagGeTqdap6wyY0rob+9/G7dUgNe45u3tLe/fv6/kYY3VajhBwbLlqOo1tsmG8/2LF8esC1KJubbn/RZ4WmMYOgvZMbrMoOBppcbHYogu45LFlpikMaJY541kw8XSEzDcDLDuYN07hs7SeSuxVKtYay7mgSWTjQCvKRZlpVvlUiGEhg/Uq6ECmjXUckoDmJL5dxTwpBphZZO4ritoaI2rwJnN2fI1Bmwtmz23hTAZ4aH+VUBo6pzTwMJfveX2e298VT1XPVZ7Pq2BU/99CaBthAya5C/Xc+6N418bMr98Ja+/8FdsvxiAqADRrBJGY1zNAdsJ2X5XLdJry/T6pC++l3IVetUEpbinkd1uX8FwmmcyGWfP1QIxhgtQuz4n3SpgNnQc5xzLMtcaXwUqtb5EGWbPbrfn9lYEjV2xor61aUyxzd6v1+tab77dbokx8vz8XN1VpWgo91LjmE9PT/z0008Xwgc3Nzc8PDxgreXp6YmcpcLo8+fPlR/X9z3Pz8+vJpKCW0vev7m5qYLLHz58YL/f88c//vFC2ETpURq33O12FzFNpbxorPO6MsUYU5NUei1atBDjWSy63XpveLjpcCHSm4gvPF1ndfESW2tJlqVYnsclE3ImBgixuOFelIxuBse6F9BcDVLF44u6kYKdAKBYoDlJDMBasM5iM1ibSvw14y7CW2Jtem9KFl9qzA1gS5beFvA8ayOZChC2aI/2vWcYfKk2kt855zPQFfB0zkvCKp81JlKYSSnW8MAvwoJBYsjNlq9+nz+qLlx+9SGjf1dsQBLO+l4z/L5lbLXH11lltfuEgWTP8P4tmH8DUmXdydcv/sIX33r/je3fQFVq3IVytJYK8W1w/Evvvf35Sl/i0lpRqyqlIlxqWzrN28e6tjrPV3Me8ArwCkxn5ZbYxDrPscbrJNpb16ExxhbQ1TLTssgYY9VS1Gz0MAwX6t4KblpK1hLjNQ7axjAVeNXyvKZEwbmGXsnwmn3VEjqNc768vFTdUQVAtTj1R++jJq7ahBicLXB9Tq3lqgkiFT95y/J0xjB2wnfscsIh4ObUgyhZ9i4ZlmiIGYzJxGQI1hCTLSrxYs1tR8+qd0JP8raOaaNpasSaquNc3eG66JZPqHXKGSD0c+JOnwHYlgiCgCYFRAu5vn7/UnTcOYN1tkoGVi2JZiw75wQ8kySlUkpnl/ovIMAvUZnemEUChOpe11hY+dV4pbmaimcv8np/9TouXqMmZXPzGlksd3295NwbYM7nz15dgwJnvnjxzQts9qqf++X796ae55kb17i1ivptguQqhqHfb/f117gOak0C5bipJmRyyszTxPFw4GQth/1e4mPbNcPQ4bxvYib54oGpa/4WJUIHPVfgfDyeCGEpbuTE4XDk5WXH8XBgnhcpQUwqpqDlma/vc0qJjx8/Vn6kuuiHw4F5ntlutzUD/o//+I+8vLxUK/Du7g7vPdutlDiqctK7d++q+PGyLFVlflmk789ut8MYw4cPHxjH8UL3sC1Pu86YT9NUXXfNfrck/jb8kHOuGVZNIOmm4iT6o5nVFmSVGP/rX/+6lo8aIwpU9/f3HA6HVxlZazKDS/QkXJZstS0A0543WLJSiqIjpsLzLOOwK3HxsXP03hVjQMBAyksRUeFcsuM1jmhrvXrnHAlD5yLOJPm+asGpnqaTkk5rqNxQl0XUxBpDZ93ZUss6duVcfAlB9Z1nGHqxPJ0rludr48CWUENEBMVTysRUVL9s+hZG/MXt9awtiFMWSenrRBU9jylVsaAYRLdinufSISJVkec6X6pLbrBaQt33teWOK5qnK2PxSKls7Q6hgRLzNvxfGzW/dA/a75u34gS/AF9vgKcSi+XBaFC6WpxXqP1WsPi/FkDldyJnqSqSiZ6K3uARbdvR9z3bG6mO8K7pR9S4NbKv5twbF0bO77w2Z0RIJBS3UfUNlZOobnstd8wKnjL66/U19yalxOfPn3l6eqrtOIwxF+6qMYbD4cA//dM/8fnz58rzfHh4YLPZcHd3xziOfPjwgRACDw8P1YU+nU5st1u2222V3Hp8fOTu7o53796xWq149+4dXdddCECo1adSXC1dqS2RUxe95c0qACoXUGvrFRxbdadWUEIXpja2+uOPP17EjjWMcS2ICwIOg80MCACRwVlERMNoaxiJffvCuYyplDqW9dQYUyk9nRdupFYnpZyZlwSpNHsrJawuig/vivXorCQZI+L+O1PA15TxV8IIzhop7zVgncEBLoPNCWcMgxd7U4+VM1VVSSxOR9d7+qGr96wMcjSxqvNFrdmUEymGcyw6n5vWfXP7iz79NXbobBGudkiJKYr05FJkASXBOxFDZL/fscxLzRVkBV/UIpR+T77rsM6x3mzoRxHpHsYRb6SPlD43k8uC9g2n/UK/oBqQDR584/J1Iat7LKFKueHfxq5X4DnPM58/fymJjU4UZYoOpi0VEbYBw7eAsQXQvzZbdv7OmROaNHmiP0mtvrOghVgppgbRq4xXQfpziEFvTPvvsx6pCoEo/y4niCGyLPEs1c85QE/j7ssFvL4mDTGoS62ut2aZrbXVulO3ebuVFh+ajX7//n3VR9RYogKbthtQEFQSvMYVlT50LejahifUXdZFrmVPtFVA6oa3gKfhB11UWk5eK2iy3+8JIRSlJvnMdcWIEuy1xO96s7a0qshlErWLYnWfc322IpxRn3J5v9SYF3ERUyxYKNlwIwu33qeYIRdCPNmSsgXjSqgInAdiwl605sgldmoK4JZMeAzV8tSEVI7NHC3H1Eohi6kz+yIxeYUA1bixZ5AVBkB+c0y225u4aYB87mLbeh3LshBT4jTPnOaFJUR2p4lQnvVcQlvTaSLGwH63P4NniWOrKv457ODpxwHnPavthmEY6fqO1Wqkd44P3cDaerrB0Q9aQCPi5daL3oEpFn71lOv1afBFY9KXV39hdRo4U81oAPRbN+oN8Hx6euHnn/+MMXBzs2EcB25ut3z48I6u82zXa/rOn4O2zRm1GdZr8PylzPR1HBIglQcynY4s84kwT8Qo1mHnHOvVirvbO8ZxVRTCRRM0G4v2htFVUg7clEEiEy0XKkiIC/NyIsZA1/UY40gJjse5uO17AUID3Tjg+w7rLcbZbw7QnDOPj488Pz9fVG60NbUfP35Es+LaNkPr0v/5n/+ZlFK15FarFT/88EMV8FCu5PPzc03cvLy88PLyUu+n/la+ZwuCFSDKAqUxzlYMQQFf45jq0itvUwUgFHzbOOfpdOLx8ZHD4cCf/vQnlmXhhx9+qOexXq8v9qGJJuXEXo8P7yze2AJ6RWPAafmsrpWlQYaRah8wpNJls46BWiIneXqvJYhWrIyUtRgCZlnjcNnhfMeSHdmKLoPrIx0JG0IBuLO6kWTKS4ml72q7FxNyLckU4WLpJksWS8wgjIDOOBFixkCCWKqKNDSlz0RZItIFAXKPFHmQiDFfo8Xb2xsfSSBAWDyxfQlZffn6lWme+Pz1mcfnFw6niT9/fWIqeg2n04llmjkeDsRSiLEsC3ER8FSXHQO281jv6Yee7e0NvutYbbf048g4Dmw3a1be8+82W+67ntvNinc3a3zXsb69xXc9w2bDsN6I4lVXhGycq2GAij3NZZ4vN1/9bt7Jl398K2fzCjylp8kOlWMLYcF5yzRtZEUaIzm7C9B89Tz+gjV69U69PI1RauhSrc1cXfiSUWxKyayxskg09+HaqG9N98szU1JuWV1zU29dQE25pufEyLn6qV3lrjcFRY0n6o8mU1o3Wa02taaV26oJoNPpdFGhpJaZuuNq2V5L3Ok5q9hIW6X0loV5bfG1z0sBVa1kPecWMIFXNCa1jLWo4Zrrp/toCf2vRog5J2E0TnhpcV7+5uL32QLL6pVUEFLrQ0fMeSKJy18mTxIeqZDwi0WqVk6xQrNK5RUmgDXn6zt7KpfWsp5TvSNGLKXLxKYKPV/F9K9CY3o/te1Ie4xf2qpRU/5W7+54mljCwn5/4KX03fr85QunaeLjl698fnpifzzx85evTPPCbieJxRY8JdQViCEQ5wKesqbhhwE3dPTjwClGfNcxLouA59BzmI6snGd9mli6njCtMeFE1/eEnPH9wCpnAuCdJw+CCanr8V48SKNjSefphZN44afL/40+w78uUvyG277w9evXQgyfWK0G5mUCE1mNI96Ju+Odpyv8w3b7S276W+/n3K4SMpokTrYQlgVbunUu80JqCOPqrp6mSe5DLMo1Jku1RWmwhTm7Cdf8TEmazEwlS+29x1mYTzNPj185HA+QxAEQl65MHFXmoVgdbywMCojq8rSTSWOUzrkLUrlyK3/88cd6fj///HMtq2zVjX766Sf+8R//kePxWMsd9/s9Ly8vF+CpYsdqwbZczHZCt9xZa+0F6Ol5t1bo4XCoCayXl5dKmdJ6dmnlYWtSS8MJbXhBSzi1nLMlz9cxg1hrHa6oDqv4r7ynMU8FMlmIZZYKx1Je02Zw0oIjIbzMROYsToMxZOukhcwSCSlz2E0clhMByyl3ZCzGe4z12KLQJYNSxq43Bm/dhbhHjo6k/ZSMXMGSMlNI0lGz3F/jLNYZJJFVknrh3BssRZn0KkLiG1Eb8fRFXKezFlt7cr69lSuWZxIWnnd7fv78mdM08dNPP/Oy3/P18Ykv5bVPn+T308uOl92eeQns9wcJb5UFPClTJYkehZxzIpe+96b3WOe4+f49/d0a1/fYbsA6R46ZOC08nU58+vIFmzM/RRiS4WbouB97+r7j5vaWvu/Y3tyy3t4w9D23N1u879hutjLeh571Zo11jn4Q2lznBbNqCbiREIe6L0aC2LL4nVe0b2LaNy3PZZmByLIM5BzxnWFar3i4v2Mc+lpX/OqB/EKC6JvWp2lsxWId5JK1kxJMK0CdEvMsn6tUlxBYSvLF1AkhE0ZiY/bt1Tw3K20MzMtMDFLuiTWEZWH3smNeZgHk+s0SW7EOSuMuDQ60l6YA1MYcgVqzq26t8jjVmtOYn/I31f3X7oCtC/7zzz/zu9/97oIXqSIkLXhq8zc9tsYqW31OvRf6/DTJc01HUvDU/WtcU5vO7ff7CuTjKIr8KtSsgHw4HPj69StAFXDWGOxut3slDGJMqeHGin+bz9aDMQo8JQ5qdYGW6jE1JFS1CCAkLVy4tDTPpomIv52iYQqZT/uFL/uZmA0LHoxls1mzGoSo7135plRP4jD4UnOusoWppMWNMTXaFlJmSZJEck7et4WeJKGAWBrbnTUdYrycP7W3lFVXHox353r5b9OQ5Q7mzLyIAfL56yP/+Pvf87Lb8//6L//Ely+PfP70mZ//9DOn0xk8D4cjx+OJHBNpXkRbVDNzF1BdgClmed9a3DhgO8/q3TtsP2D7Hus6jLPkBCkEDscjn1+eSSGQX44wBzbOcuMcfee5u93S9x23N7dst1tW48i7Uk33cP/AdrNlvVlzd3+H7zyb7Yau7xj6ntUwnt37sliZIjBgynMUbdbLy3hrewWe0lZ4oO89333/gbu7G9brkbv7LUM/MJZKEy2FvH4Q19bdNZC2/1awMVCpGFPJckt/81N1X1MVBJFJ/fj4VWIy08zhdMJiynShtHSVZnLd0NUMr/Ll1DXUx5yKNqRYswFS5njY45DGXSkEciHqiwK+1MWfXdbGH9Dw2pV71YrCqvusFqEKaWicUbmdbeZak01w7kq43+8rN1MVkTST3yaA9Hm0tJ7Wkmxd7zaE0FYGte1CWh6sPlM9zvPzM13X8f79+5ocU7BVq1MBV7+rIQcF1mvLE6hJFDlNoaqY+l7rxpfF7TzgoPmevJTqM6uxMFMI60binjHBaUmcQmIKmTkaIoZQAGFeIpjA4KAre3a5NgkpVT5yJtLx8uxK57J4p5wJKZf4ucTqpMGdcDetk86bxkpXz5ikzXEb89SIQ/v3X71pHDVlAcIQ6/P5+viVTx8/8fjxM1///JmwLMTDCRMCI0Y60LpCyclZAFTDInWTk7ExY2PGOIffbHB9x/v7e969f1/VoKy1bMeesetYDQPGS+PD51NkmhNLhFNKxBSwhyPdshAznJaZoR84zhOd73h62UkbkNXI9maD8571RrrCjv3AOIwYa0uiyWC8w3grMdfNGu8c22Fg7Dq8E4GW6fRXNoDrOs/d/Q3WGv7H//G/4ze/+RXOO/q+NFLrelHz/gXL8xo825/2c8ZoUussWbXb7/jy+QtfPn/m5fmF0+lECqmxhBKn44l/+Zd/wXUdq/WK1WaDM5bB+coIcM7Q9R2bzQrfed69e8dms2YYVmy3G3HrTLE+o/SZX+aF0+EoPWaWmcPLM95Z+qEjZ1immdNxJsVM5wc6P+CcP2d+r4ZOG0/UKigFRLXKhmHg/v6+EtOViqStMO7v72uF0e9//3tOpxOfP3+uwLndbqv8nCaOlO+pVT7XsUsFb62fb/mYmvhpdUg19tqWcrbUJZ3MMUZ++uknnp+fubu748cff6wsAu89X7584fPnzxXkgdoORMG87cFdp6Ap1CRKzNlQwFNFMi7magOcakUUWnqJj1ubxULlHEN0lJhXMsRsmFPmZYrsp8jzBLvFisxdUVKKx0g3J9adpRst3ho6K2r0Dsl2S/ioqD9ZW6v0YpZWyUtKLCnh8bh+oPOOfhwYOi/nZ8GmxBQWTM4sceYwyf0a3IAzjmwzxpeFQy3gvxJATcqYlMkxksr4Px5OvDzv+P3vfs+//MsfeP70mac//RkDDF5oQ9txYLVeY5AeUZeteRp7Psnz8SHTLRnXdQz3D/hx5N1vf8vDP/x7pnnm+Vmq6n7z4R0P2y3P08T9Yc9+f+R/e555OQRYInERKcH9PGEtdP6rcHcLj1rGcul66x1+kDj/uBrpvGfoV4zDCowlOS8Dq+swnWOzWvHDd+8Yh4Hfvv/Au+0N69XIw80Nu90LYXm9oH+jwqgMKBUh7Rx9L8mZKm77b1ri3nhwxlQA1Z+cpdeRcCxnaV8cX4vjZqQBV8xZMt5WWhUE53DG4r0AaAgLxmR852vdNjRZZWfLonlFywiRYISXlzuP9+Kep2L5Kkle466ZQhK+ikh8K6jfVg21PV/O9I2zJdgKwb7FgdStTTJpjFKBuxUxuf5pz+/6dXXNdeFSq9g3sW4955Zgr3FQLd3Uc1A+qlquOgbalgitFsCrMcN5rEjOvR1PTU7VqO3ZWp36Oao32eYMsu67GWQ5a2M31U4wZOPqcTR/o8kiiaVRF1IDmNyAfPUCzomiXMDdFnC19W8wNpOyegmp/BbX3lmxTFXX4Wx1t67zLyQ+mmddLeTyYzKkJRCmiTzNmHmRCi3r6UxmbQwb57BkfKF8nW+bViKVNStnugx9zpJd7zyu86y8xGWTk0Z3ZOmo25XYZO875i4U91qa6vlcRE9KyCWHRMyGnCILIvMXY8AsFusdLriyqAd855nnwDQFifNmCc2Yocf0Hdt5ous963HgflwxOomNLuNIDG8JdL8Bnssy8/j4Bch8/vxZWlxsN7x7d4828KoW5JWLeh6g3w6yXnxOeWllROcstd0///wzL88vwg9cAr0/N0SzxdLrh1HoDs4RYoKcmE8zhkzvndQWG8Nuv8NYw9evT3Rdz13pwClWqXTyOx6PzNPEPM1MxyNxCURrmK3I1Zm0JhuYp5llCex3O/788aP0+nkUa/fl5fTmYG0tN2ttbX2g0nMtX/X29pbb29sq/qH9qdfrNavVin/4h38ghMCHDx9q3PDTp0/sdjs+ffrE09NTJby3INoC7mq1qqCq8dXrih4FTU0Etdl8jZ0qcyDGWEWaFRzmeeZ3v/tdVWQCiVG/vLzURJGC7Vv9ZVq+aHNSaMTZotU/MnHrhIUKjFpKWZ9IlsReLhNQRYox8t0q7mEyNmecyQzOkzqH7UZWZpTKpVx6tocFUmBwls5ZOmsYB8/obRkHCevAEoVz2QQfoxahGE/vHX3X0/ej9IT3viQjpSa+84bNaiDmjmHwbG9GrBELSzt7WiPskJii8JPrAvTGIlSwNaXEfJrIKeGxbPqBu3HFD9sb/GniO2vYpci9NcS+p7OWh3Gk947t0LPpOmzOdLo4lAVL2Ra5WeR8Z/BYsvfMvSN5mI87nj7/Cdv13Nxssc4SUuTL8xNTMUxMjtx2DsaOOwsPJIxJBI9Y3M5JF1FrsZ2X/IZ3Esd0FttJ+KMfpC1KypEwn9hPM7/7+JnDvNDd3tBtN9yuV0zzxGYc6WImHE+8v71jXfDhOg4Pb4BnjJHj4UDK0p1yt9/juw4061TNRHkS3+JA6US4HP9vaHlW4JT3T9PEy8tLrcSJMeKdw5timZUV2nVSmglIoDkl4qxanJYu2nJ+ctH7/QHnXBWikFihmPtnIm8gzDMxBCATTYYU6HvxoWJYSDExTcJrk4SLXEIIbybcAWq2vSWIb7dbfvjhhxrnzDmz3W757rvvava8zXb3fc/9/T0gSSclnv/rv/5r1TnVfjJqUah113bv1Nfa1hvfIsgrgV5jlyo7dx0zvbZWQwh8+fKlipzoMdrMfdvnpuV16gJzAegaSzNn2rPIy4EuuhULKVaUZt1raums2KNsjDeWump9GjKdtQQH1o8MfksEplK+GaYjKYigiFYfdb6j6yxkZS2AKarMRhNxOdeu3QZpr+GsxzvVXXVNAYC4/r2TJcJ3jiH1QOnDZM7UphAjLIlEJoZS3nxBx7m60iySjzlGyRdYz8r33A4DS9+zNYaNFkl4z2AtHzrP4D1b59lYiwO6nJV9hAEipgo1a4JME2fROXbeMlt4XE687J4ZNltu3r3Dec9yOLLMM0t55KK9akid4z4lvveBbCyzz0RryM6SnRUA9XLf6EoCyBtMJyyM3ou1voREiAvT6cifP33i6XhiXGb6GDgtM+vOM40nvq43rJ2IUWucPr/hDb1OGHnPZrslRsm6//EP/8p+fyDFxDD0vH/3wGoYz4OsAchXwHi1vXq9PPyMJGzU9ZSqmyCBc2vph4Gh68XuWKSePMZYBQiygZyS9OrOharRd7W2mLJ/sYoWnp6eS0wv0fUdLy8vBUDLTcpZiLcO+k6sA5meiZgWXnZP/OEPvz9XdBjDZnPLdnv35rW34KkgM44j7969A+Dp6anqcipRXOk9arEp8OWc+fr1a81qq5DGOI61Bl5BSsnrOlmuk1jXSaT2fNvqI62CijEyjmNJvnVsNhvgTBtrj3EWa4lVa1Qt4MrRbX7rfXzL6lQw075D1ecuWdGz1Vgd6jI2FTDl81oSWJXnVVBCIA6QssvOZTKWzSDqSCdjmYofbwswal17LdNEGtDFJMUa1qnbXvpX5ljHlp6lLzSm3nfS17664KUe3iL+rxUQdFlKgzXiW06enEUkJVupuze+J+WET5fZ9pwz83Ti8PLMab/n59//kTAvDN1A5zt2hwPxcMSHyI8P95hf/5r450/E40QHPJDpU2RIgS5K2MQXGp8vnkAqhSw5C+MFY+h8preGAMxZrAyLtA83FnwvJZomJ6J3oOGzGOltItnAjVl4nydMzoSYS4I/k5OTDgExC1jHYo1GK/2pnGPoha2xWMPsLKPz/Ow8o/MM6zX93b00l3x3z3a14sN3H/j+3Xve39/x7t0Dh+OhGJCX2yvw7LuO+/sHlmXm8+dHfvrpZx4eHnh53rPdbuh9T/fQCd+z4Qnq4OcbwHm5FSGE+lDPMTst50tRqmsMUoUy9AMxGzhM4j6FKHGVEghTKTuD9J4Zh7EIcnRALkAj/dk/LRK7e355wTnHl89fOB2PpFAGeMp0vWUcPEMvCuMyZCMxznz58ok/l+qgFGUy/Pt//x/Y/MPt64nfuLJtHHKz2fDrX0sPepV4077ZCn56P758+YL3voKQJoyUwqSlj9qdU1fLa73NVgmqjVm2br1ajpq4ORwOkrQr37+5uamhhIeHh9ryuG0wpzFNDVe0Lr9anG0sVM+jZQJcj5f6rDVDXJBSn3+baK5gW5dmivUnGWGrwKljp3wjZRFYHrxYkmndEZLlOVhSSFKKmRdyEn6ocxlfwNMaSCkQogg3e20il0LJaGvcWRpxGGPoXY81nlU/MPS9VCW5Enaw5vy3zzVWSxlPobRdTlG4n8bYQkB3ZCtiOd3iYb4cj9PxwMvjZ778/Gf+H/+3/zvH3YG723vW662Aj3N0S+AffviBXw8DR+fYf33GxcBtjPgY5JJMeSZJrnOwls7Y+uxTzkQrUnKj6Vg5y5wTUzKYZPE5YEzEukw/evzQ43rhetp5IR4niIG1TTiz8J4Tv8lHiXMvWRY8m0jGCx2t8DWNd/JAOo+JSWhRa4M3juAci3E8+sCT6/jqI/3NLf1337G52fDjjx/YrFf83W9/w7/77jvub2748cMHnp+f6Yf+FYq9Ak+VKTOGmoAglwZWpc57nmfwHtuJa6GDvgnZv2mB5Qsqg3zaGFMItVLCpbE6g/Rw11a/tR64TPCY0mWwv8n4CVnaSd1sLyuGuqk1wWFsVXBqEyrWyJKvwWttsAVZMnjek0Mkh0WEJYJM/viGWX9tlSswtBU1Cl4KrGrlqRJTK7rRJpQ09LBer6sAhyZrFET1+bWloa1l1yaI3mJFXLvy10kvDQXoNSlQX7v0KqSs1Kw2w39No9J462U46JzJkVPL59df/XXBd5AJlS8+UGOj5x2aKlAswCXWrHdCMbIRLAlrCo9YA4eGc7KkJB6TKZTHJJzUqkLWnJseWlx2iVsa5alyjow1pjQ0s6vuUk+jXKN27NTPvZ6DmbQsLMcj837P8emJ027PqhukvLHr8H2P7Tz9akVeAmEYJYaYSgPFnDHek7tOikdCKtJ6YHUOlRNM9bKTiDNnizUSb/bOiiHmtNQ7l3kGyWeGLmPCUgog5F713mJzRkWsooGos78sqiZCFfOwck7+OOGSPJOUHN3pxCaKl+CQ+dSX56BqWCTljJcCDF5vb1CVeh7uHsTKWN+ylB45ne9JCR6/PDGdJm5uNtzdbiXW03WFjK4TrgwI05Liz4M6JZ2E8pNi4LkkO/a7HXPRtLy7vRWrqDTwyiUori5+KiAaU8Jby2qQoLtznn4YGMeB+9ubWuWiQiNSAZFZolCf5PlmrLEM44gzhu2qZzN0OG/oO08C7m+3dOs10xw4HOeiHHMixCTk+qutBRklpavMnIKetbYmcV5eXvjf//f/vSopaSdKuWdngQYt4Twej/zqV79iWZaLthn7/Z7j8cif/vSnV8metpOlZs9bsG4z/cuy1G6H+u9rPqgyABT02qomLRDQRUDJ+m2Z6PX9mueZn3/+mePx2LwuAsOOAjCGwj5qs7zyf41/mnxenGVhavQO8nnHxpTnls35WKJ2TGdEuLhLEbdEIrl06szkqqmWSaU7+hySNInLlpx9VbuXwwroWoCSkR/HThJFnafz7kyf0rFT6HSqXZsKaV7zA+06IdfpylgxNaaKRjjKTZpeXnj56Sde/vBHdv/lv3A6HLhZjdiHW9y6p3v3QMqJlTG4/ZGXT4/svMdl8KajMwbub+Bmg5sW3NMOswRsCNgUkQ6fmUhmyoklgwuG2S5E4+lcD53jYXtL9/4HzNBjU4JlYdUP9ENHGlbEteV0WHFcj8w7y2B6Nh24lLFBwh8xGUJCejyVsBxBPasS5zaG+OdnopXEcogZFxN/d5yYMRzDwpQTAwlPxKSF4/MjL2FhzIF4d0tcZnL+K2Ke1lqGvrQHtdIWVdxzEWU4nSZyinSdY7MeyYXcW4PGRoP15zahuX3g+hxzC6bnlrRLcfsM0A893nnCvBBDrPGdlEVKLKZMiEFkxZxn6HrI7sxl9B3DMOKdZch9TVrM0yx0o6PI3BVNsWLtOrwRPcW+84UWIg7g0PfkDqxdSMkQXKE+5Cj3p9murbeWHK8ZZrW0lIo0F4EF7YCpYKbCxtMkZF0t+WyViFarVVVaGsexyugdj8cKRG13TrW2W6u7fV9/1EJugbO9vjZeqf/WBUMBVF16ZRq06vXXAHo8Hr9R3170HA2lpK6ggVqknBN2bWhUHfrq9qr7Xx1906SVxM03VkDTOXPh5tvG6jxHXUWgLedM1N8RopWYvCuHqkktU7zrIqnX9V70Op0pc0g/p+bnee7EJD9wKUR+jpadrzVrELjZcs7EeWbZ75lfXpifvrIcjuR5EivZW8xqwGZw2y3eehhHZiNE9qDFMcMAmzXGTrA7Cp8zRmzJhGkdvkrXxazeXRLVfmcZup40rMidl2uKCW8MvXPgPNn02BhxRUXfeUtnOlzKOBMhCRDacl25JOayNLAq4QwJbYQ0SVI5JlKM2Aw3SALLFtqTsgbIiTBNTNmw3GxJYSGn+GY2+DVVaZo5PD+TY8ms2lL94B3JBp6SmNIhLqQYLh6QZAwFfLfbLda5yqHUAVcRkLOruN/v+fjzz+z2e8KysFmtWa/WbFaimLKPUqpJKUHLGDxa/5uJMdfMuf4MfS/qLNuNaDCWpm3Bi4keYihZdW0L7EWxfOiFetIVfpm15T3L3Wpgaz1ziJy20g98szmwhMjt7fZNS0qBs+VqquvcimgoPUkJ7tM01X5HapmqFdgKGatr3nUdy7LU7pVKCToej3z9+pWXlxfW6zW3t7dYaysFqa27by1TDSMomb9lCdze3rJerys4tgtFe23nxn3Hat2qpdvW+rebntPljSwAYc+Wp7x+6Qa3n1crVL57BvZsJE6dNfFSF2RT54cmkkwOgIC2NxK/k4pxiDlCykXhHHHvjRP2hbVqY5bTOUvfCVledBG6ztF15XpyqAlQWQhynTshnoWoU86F66n5BjlX+Wwq19OsFNd3J2dxSVPELQG3LMzTif1pj/UG/7Unpszjnz9x2h34+PTI1zDTp8SNtfhssSFiThNmnnAseALeRLzNJFU0O+e5CDnyEhIYKefMxnJ82vHy82dS37FsRvCW08tE33Uk44imYz4emF6OcAolZl32KUFOXFnMshGpQIoyVk6JbI1Y4BJhRtNslBBDLN91IWLmmTx7wmGGKfCnn77wPM1M/+4rN93AaZ6ZT9P1KHtDGOQ08fjzR+IS2Gy3Us7UeawmXnYnUopMpyNT0as8zTLgx36oWdjvvvteeIBJ1KVrTLdehI5UeHl65qeffmL3siOnxHazYb3esN1usMYynaaqTuS8R7h5Ij2XYi7iDI6+HxjGoYoKr1crbm+2dN6zzBMxBELwLN6yLIF5XiBnOu9xrqNzlvVqoHOWvvDsrLM412GdZ3tzhx9WxAxLhhAjz8cTSwz0/epN8FRLTMGzVQ5SN1cBVIEOxALr+57b29ua1VZrXSeSglAIgXEcL5JEh8OBvu85Ho/89NNPeO9rxRJQeaQKnhqTVEFitYpV8Fg5nbe3t9zd3VULt7UglTfatkXWUtsY44W6/FuZ/pbOdHEf0Ti2qQAq4JiuPnW9teCp6keSvFFqt9KG6o8eT+XtMjgKoTsJX1GeQQE3qMkr65x4KfYcklTgrCFMZ3GlTLjvnVCbABEBoUjpFZm8LILb8xzEipJBJdVznS9MkkIYz7G5b+oH6t/tLUmQIiZG/BII88J8OvByfMZkpbFJpdjuecfj1y98CSfWGb5zPWM25CVgjidsmPF5xptI5yKeotpfqK4uScxxzokpRAyJfg6A5fjlmafgCUPHdLchO0fv9+LtWstkPXk6EZ73cFjk+TtTALnkIBBmA8ZUQr5qtWaTSaV1h4uQOFOqJM+fxLuIQcDz5Aj7EyFn/vB//BPxTx+ZH595v70hGpiPl1Vv8FaFUc7kRcq14mlmSWAWhwlSSbPEmZQjR1s0CcmFmiA1sppN/vr1K845lqi9b849Z1wbB0d6jauqUVcApu86vPOFGH8u37PGkkyqiSMZT6ZYnoOIqXb92cJrgucqCID3NdAO4GwpV7TUxJRR/p4rtCfnS7WVJ4VInFQ5eyaEiHM956l3ubWgqi6yWp1qZamr22pkqtut1VEaW1SAaS3Pqp1Y7vfxeLwAyDbBA1xYwW25plqw+lm1dpWP2lrQb/F4r6+3BUddJPT6gVf7eauuvR2bGsCXQzWuKwpYjZt+8RCaP9TPVQutxgULiJt88Z4UhrjGNdbTMbUdBUmEPuozNpI8ciWJ40qVjDFnzUmpDhItWpW/O49XDShchrqUPypxUL3Oa751fmsYyn6zsA5cSnRJPDq7P8DjM3mY4BRIIWEeH7Eve4bjkS2ZNbDOkVUGosMEQxciXdYuoBZniiWYs6jnG4MnEzUH4n1JCllMTORlEa5msdyTsURjmVPmsEzkecJNC3YOQj9K9nx9ADFjYln1YpI4dywiJSlJcUI++wAqNJ3h3FMqRSFph1hCg5n5OBH2R+b9keV4Ek7pX8PzNClhpglzmjgeThyNIVvpXCegLg/mxVtMJ4OgW4mk1LgaZbKlzL/8/o8Sy5wnliXgSiWGtYaxKNRTrIBlCbw8CcH73bv33N2KZaM9csZxFCsmJJyfSATS1LSFcI5xGHj37j2bzYab7cgwDviur+6PLWBvvJRgTfPM4/MLhswwdNzdbWVQlb7cItLgGFYjt3f3uM7jxzW265m+PvP16YtwRnd75hB5eAfjuHk9adshXazFtu+6ApP2Wb+9vQXg8+fPPD4+cjweeXl5qf3Xc85VZFhpXcrpbPsMaQ1829ZYe68bY3h5ealgqO76zc1NlZHTxebh4eEic397e1urjNQ6belPLQ1J491qnap1rcAPvJLGa5NOlzcvkU1ZBLRbZBPbvBrFFwmg88v2bHooMCpY2ZKVx5CzK/QXJ1l4jQGnwgjNkLMVCmWGOQrnM+SAtbmYsxFvDZuxo7OWVe8Yi/r5ajXivKcbVriuJ5MlDJAzulNjLNa4IigimXtJeAZStJCThJW8zKlWJep8zZdxOgPYHOniwhgX7uaZ8XQk//Mf4M9fyNaSjPAsx5cddpq5Oe75FZHRwK/igVWyLKeFEDtchlWyWCydkeRYSgKakcyqWId+MHQrg7EO70YwDh8SHI5gDdk5UtcT+xF8z26/56fnr3A88P7xmfXzDrzHdJ2searAl/JZzanEOhU4oSwUAMmWZKPFmK60KIlgwM0zZreXPMpmLYbH12eWj1/Yv//C4c9fJC47X3Z0hW9YniYmCOfeNclAUKKdl0GXCofLdp7RgC+lkmfZsSMxRE6FcygVGBJ4Xo093rtzq9QYmZelWoOtdQNNoqOpvhBqyNlqc85VEOj6vvZFUQtVy/W0zWxMqcahtNWIyRFbklXWlfpY7+mG0piq81jvyCTm+cQ0LUynE/MSa5uBV9P4ama3iZq2uqcFnWVZagtktUQ1vphzruIfWj6pYNRWF03TVDPwrZXZWp6tdakczDa8oDHX9lpasGuBs702/WxLjdLPqzuv4KmAe86KX3YlLYOSSkXhbJWlxsJsLTZ1v+uraknWMGD7N5dAm0Gr0TVFVIg4ch7Fvq2po4J3BoT/mRM5R0iRaA19cOChS8IVpngQmh9w1pFKokmTLedzbOljOj0lXCFtY0yR4HtDpOcXLE9bLM8hS5Y67g6kaZHzK4DUnU4QAj7OdCYzAhsiY05MyTJHcFg8IoTiAVcwwpZb6rNY39kZci8Sjp0420JnKmplqdzDKNlA5pw4zBJTjfMC01LoSWXxU/+7nKvJDYgqoDZJPfXoDUXf1YAtJH8TJdOfFtEOjikRppnlNLGcZsJplmz+X2N52gxdUVsJUeKVGck4yhMU3cGQMosRCsnYD/ihLyKkA2AxZsLYXCk6OUVpUJUTnERt2ztXdfU2m61YFZ2vk0ubpAmg9vhuxllHtEU4EbFEjDV0vWO1Gllv1tzfbbnZbjDFHcopSyLIu2IVJDCuembOO8axk1pj0+MMrFcjq3GgGwbWt7dgDId5Yj6eeNo/8/XpK/O8sNtNhBCZ7+dmNp63FgiuuZQKnK1GpgLfzz//XAnn2imz73tSkq6cnz594uvXr3z8+PEiY66g3AKwWrQKWFoWqTXz2+32ot+63nu1WpUWpYr2X758qdanZv71R4U/FIhViQm42F+rT9qGD+C8KOqWUiYsC4tdKhdPOlr6xno0knEtep+5NFY7Z/TPccdcZrfGFSnZ64zQfOYIS8g8HyfmAKfgmKJjKdSYmKVbZSq0JbVAJbsrrvASFixwOIoFer9ZETeGGBOblYwS14mQojWWXLjE2sHRlBXAAM5LkkkEarpyHefYlywY7TizJez0GlRdjnRpZmMiH0bPsuqIVlp9hJSZo9THBwzJeJwHly2ezDYnfMnKu87hsmHMAkKu3OGUpDIqZkhRAHRx0u4E43BZkmk+zLCcmJj4+afI3HXkfkX2PbvDni9Pj/TTxK+PR4Yl0GHxROkUanQRK1OuLDh6zzSfkjVJXdqv6Mw0ZHz5jD2dyE/PHA97/nX/zBITq8fP9LOEDUwIZGvOOZpme+2251JyFRMmJWJZDYW1UcChLOTRZFw2ImwwjBJvHAZS0jhRpuskVrTME6cwy0q3SHxiGHrsIKVh682azkmNr1onWpVjjSZcikBIjNQIl8nFcnSMq4H1esXt7R0P93cs88R+9wwpY31HN/QC4GERJjSlZthbMB3eIv28reVmu2W9FreqX69JOfM0HdhNe14OLzztnlimwHG/EENmmZdvhTzLgH5NQq8DulCH2rLIjx8/cjgcajY6xsjd3R0pJT59+sS//uu/8vHjR37/+99fkOjbZl0qSiycwvGi8Zwq12+3W+7v7y/0RbUWvuWDagzWOcfT0xN931ewrVUlDclf47RtBZECcis716pFtUUD13HiECPBBGLnyUmafjkn1kyNVUpldwXQcmCZ1qZYHRVQ1TpRG1UGdcqGJRhOS+LxeeE0R4Lkk0kYAq4YNwKdAngyjuZFNQEip0nCP56lHNcJ2OfEshRhkiSLAEYEnbV5XHng5CiupfcSSrCFyC1G6jlpqHkG3aRj7Lkf/cVYK+DpTOT94ImjJ8RMzIklR44hFCvNl9CBsAgMCc8iNnlnsZ0wXsZ0jh+CeMzWFkOQjM/grVaxWWx25Gzwy0nAc7H8edlztJalWxFdxzxP7A871iHA8ciwRDoCRQ6bRAnr6Gqof17gm3oIlE4QnH9yIVLmjDmdwBqOOfLHTzNzjPzq6577eSYvi8RDS4jxentDkq64DyWmdP5Sru4y6WyE5pRZlkB2s7Qm8J6UUyXsSgdOx+QsSftJB8ly9/3AerOh8x3bzaZUFJ15gtcUGO/Oun0YARTfeWlMV7LEcsyezWZLGAa8l4D8apCWpqfjgePhwDTPokKTJaM++I7OOTYlpLDeblmvVuAcxncSWoiR40m6BMYotfTnxMVr1Gx5lO1rbbsLdYWVntRm4FuLUibFJadSga1WRzVussY59bsKyioTt9vtqvq77vO6uqfl307TVIFPyfXXVUetK98q0bfhCQXk9vs6+dt2H29Vx2j8OoQkyRa1JjQBpMmgnKllKBVYc7U+WmEQJdAp2zNnaakrzQYLh9jYpi+DXoeB7ATEklThuXIe3jnR5AQ8GWdKz/gSF6jlq3HBBvGAclkDNCxLSgKg7aTNZ/qSuO3nxeA1h7qxztrNSOwxW0tyhuQMwRoCmcU5oisUn+jIyZIJkAMuG1Yp48kSs8SJtalFAAX4TSpAmoTQnpPEc80iWXZT3L0+RTY5cggRv5+FTuRmFuvJYaGbT/QxsUoigdc1oQtT+wxdjRF9We9DY5mrFS+u+1mGr0+ZIUT6FPBhIsVIFyM9olWa/m3gSVOHK26IDi59WhnAyUOLIbHb7THzRMhSWZBjLsIcQrVZrUYO+x3P3hHCwnw6EkPg7u6O7777QN/13Gxvqwt40fBNkxBZyvxu70R8Y7UZRadz6BnGXlZaPJC4ub3jx1//utzo4lqFQE6Rn3/+E49Pf+R0OnKaZkKKbMaRzXpk6Dse7m7pu4719oZxtWaJif08E6aJl+OJj1+/8nV34BSkNUJWods3Ms8th1M3tahbubj1ei3WVXlPAUqtOTiXzSpJvs2855wroV6rlnQf+v1lWXh5eeEPf/gDxhienp6q9ffDDz/Uz+g5K/Xo6emJ5+fn2mzOe19bKmtCT8FOgVyBWvel59GWpOqxWpC9dt/bLWXJ88xLIuUgteO2WFlCrqyKW5CxFKX7IjwsY1gsUksGW9z6JCWYObtieUamWSzO0zxxmqKUIVt/3oeBvkjHxbCwzEG6TDgBpew8ue+wQO8EVLeDp/NgkCRqSgFs6RtlKCLLoB1BTU5Y5ZmW8sCYEqkoJqkX4b2rhkoutKWYRLotJU/m6l46D11P7nvmzrH0jpOH2UHIljl7YjZMsyNEyxwmTsuJIWV+XDpWGQbjWGExJmLcLMAphiU2iXJ8ThlMxAfx38N+KYtXR8Zwa2Z+ZRbyNLN+3kkb4wTHbOgwbI3h1jo+DCu+7zpunAUnVr5LErgUO+4K1Ezzu4JtCX8YjWEXEWgytyERToF5OXFzeGZKkdtguMMwhoV4OpCJJM8r1tcr8KyGVPPvMzCYy/9nAYklBIzNZcKrYMeZ39j3PWHpz4rlbsFAJYD3Xc+4GvHuDJ46qc4ApGRzj7UCOP3QsV6PrNerojAf5LhOdD+dNWJ55izti4OQ+pcQWUKpijVnqo6Q6wfR6ewHun4gLoG8yOQIMTEvBTT16Zjz5H1ru06qXP+7pSC1xPlri+5bP61VqsCjiZeWgN7GLuHcebNVQ7qmEeWcL1zttyzJ1rptj9e6lNfXoueo59V+55ubUctQqmxMqbaRZGBx2cq4E/k3lSQEaLL3apw29//sPRT6dBnXRl82Z10FzUZpN89cXGOxZEsQoJyrMzCU2mzvjGpXkFIkRggxFMvTFBaLHETAUmOx55POxZJLxQKV61PgbMdVYSK8YXmK5mUHXrRKU+eILhNtJiLZ9pQMITuCsczZMsUC3ra0ci7ULSwk58AkskeU7FOZCilL4JOECdKGQzBDKFadS6xMZpUT47IwLREfMy5lOusYnWdlYRxgNKaEDRFBknJLcol316u+wK3m2uuDpHrPqsTlM/QxMcTMEMXa77Ojx+DITbLotXf52vI0htR1pD6S8ecBqJnOc6qLiNSVz9NEjrLiRsBbx+ClYqcrKu4hLJIBt4bOSRvjd+/e8cP33+N9x2pcN1lId0EA//RJVIS6rmNtRPS07z3eO969e+BXv/6BsES+fHkhLInD4cg//dPv2GzWfP/9B5xznKZFVJWmhTlIhm+92Ur9+GbkdrOi6zz9uBIL2DjmCIcp8OXpwPF04jhDpAM30o834kJ1QLb4rq/xF92uuZxwVoZvrav2c/pZzXYrqF8Lg7S8TDg3eVNAm6aJ4/FYrUFdiDRppNavfk77B8HZktSa+ZeXlwvAbPsurdfriySVeg9wBkNdHFp3XL+n59US5q+rjoy19N1IZ6RB6hJFv3Ka90hlVI9zYtX6rpRXWtFazU5LBTlntK1wARWIMme/ubOOzSCWJa5njpljMJyCYYlFQDiLipB3Dm8NWEcq7aszIlPnnXA7131p0eGgc+CsxGVjhuM0M4Uk6vRWxI27vpDgnaPz2uHR1mmbtfd8MV6WJRIWbYYoXGxlloSkiY6z/+pu7xl+81uSseRf/4q0XpF3OzgdRWTZSljDmUAi07GQs7ixycHiwKxH0mpNtIapEwqj8YDNeGvprcekRNgdSHOA3ZHhqZRxJrEV39nEGhGcntc37GLmpyXyGBMr33HbDWys5e+GnvfOMZJYkE6jHfYKxs6bAGxZyBqg1V+m+PAao12Jc4Ixjv9rv2XJie0SGUPizsjzDfZcwNtur8HTiuJz7vwZyXNB4Czgqat8yomYE6clESOigm0MQ9fRWwdZSjbPrSYcySIVFsZwe3vDw8ODfKYTcWJNWujEljjdnsPhKIkdJxUm4rpabm+3/OpXPzJPCzk5TieRcXt+3vPw8MDDuwfAMC+B0zQzL0JuT8A4rvDOsl0PbDZjAaW+UJwsIWamJfFymDicJPOassO4nm5YC3hK8xvsG3p/bcyzBZKW7qOfu6YvXasvXYNn+6MJIE3S6H7bdhkKoq3gBlCVmNSqzCU80oqPaOJKQU1BWz+n3oFeXxv71GuRoXW+5r4XDq4ulG/HOcugtxbfd3QmEU+iaRBjIizCxkgZ+q7ct+Lx2KF0ZKSG6c9WcJIak0wuPdHF0SdLwcTYGTpvsIMnYnjcLyyHQEjSDjslider0Ie3ksQhiXCHN9A7g3ew7g1dY3VaC9kkqVJbFvKSBHmcLe8hrS0MdKVf0nneqrVZ3NasGf4S8qlsisKZxV8aS8bgNhv8h+9w80x+/17423OAo9xLp9VBBKKKZZDwZLLNRGOYV554s2Jxjn03kKyRMJ7N9N6zHnpMTKTumXya6KKhf5mLslKEnPBZiPeDs6RxzTHB1gU+h8i667kdVqyM5TtvuTFg8kJIQQRKeBvMzsB5tkKr/VlQVGPkGgcdEBUoj8N1K2JOmDRh0iKCz8aQmnhru70JnrbvJT5utJ63VAch3C6TYZlP5EnoGqL2IlU+XdfXxmR919NVCTJX2jVkxq4X0NreMK5WojTtOpSv1upBtpMyhpKcInOcDmASNzcbNts1KWYOx4lliXx5fOLp6YX98UBfej2HZSGlwHGaQdVnMMSUxaJYosRqjMOYRDSJyMLhOBXxVYP3A+O4wdkea3pSSEylIZx9I04HXIBIC6TXr7eWXQuq7X7Oc+B198vNZsN6va6usoLlteXbApSGCeZ5rpbwW0kftSg1rnk6nTDGsNvt6mf0cyrQ/NbWln1eDjl7Ac5vcj2La32W8GjeipFkDREIZX8YiUEa54VgjcE60bnMxRUzKWGLZ+WMJDM6l8k+EzGYbInZsJsSlqUmHEDcdlfQUKpkjIj5GgFNWedlHyShAqGJVONLfkvc34TkDjDCKjAGxsGRksM7w+CdEM+TlGuqmljWevaU69ihWFLZ5Gqgtpvpeuxqg91ssXf32JTwjy/Ai4Q7Qql2SpE+SxFLyoIBY1kssoXoLbEfiDd3RO/JRdTUDR1ms4YQmDEEt4PDRO8dBkMXEzZZlpIa743h1lkGC4vrWWXofceqG+iModPkVyxlq5yZtjVnpGEXyQmSLhJE1MIDyEUNK1eNaBlnCQesykc1YOKdw68G0tBjUpAb22yvqUrO4bcb6HtKXJbOe8auLwIJYjLPT4/kx5mUIERpA+q8Z71ec7PZ8P1339N3HcOql2z2MHBzc4Nzloe7O8Zh4P37d9w/PEjcorgYy7IwzVOhx5zjlL7rmcLEqVijX58/Mc0nTtOBl/0zXTewGu8Awz///l/459/9gfu7O758/co4DGy2a4ahlxCD6zDGEXMgpcxpipAnAaNZYk+nkJljYo5J6CrJMI43ODfIAI7ipj5+eWQ6TTj/2vKsk7vE/1oS+HWWuU0MXVtu10BS2QcNkf3du3fc3d1VS1Hd4TZp1AKz/p1SYr/fV9m8VnFJrf/T6VT7FE3TxNPTU2UGDMNQqUctVamNy+o1tWWdrTWqFmjb0uNiseAMmwbbTKHzvTW5pHnnCessMS4i7Lva4v2AsQ7nBjCWqH3bU8a6IpCcCoXGGkYr1UNLTISU2Z8CT5wKvUUmhaNkgJ3FWmlgFlyJNRfNSmeyGCEpE5ZECHNpHdNjHbjOYV1HDJnTXDrDzkdCDGzXPbc3wk2+Wa1Esk74P6SoLbDPhfm53CMMxCglo7Ekcdobacc1/u493RLofvNb0nqD/fRI9/EzLgf8PEPKrBdRJbIpVwpQNCL8cXCG0+BYbjZMv/k74jASnSdZi9uuse/vyfPEwTuOnz9hpsD68wvWBcnYx8SxsCGcNfSDIxnLd33P4juy9SQnnkk+zULZIpGzcKCiKSWY5XmYXPADKd6JRmC2UpeK+5FNIhfWRKzjR3jfPYahzLsJ4bCPQ8dwt8X0HXa3g+UvgKf6FqbIT2UDTkVSTYl4ZmTF1fOSSHq1CYw5T2wVE/Zdx7ha4a30UBdpsq7GomKQFVSSE4V4XtzJZQks5fc8L0Wp58RpPvLysuPr1yf6fiQlj8FxOB45noSG8/LyIn3MySLoHBaWKFaAKY3jZFJmISIjE38OiTlmljIQc02COUkOFK0x6bMdX8XpdGJ/6+etrQWat/ig11ZpGydtK3fabP110uY6uaPfbWlQ1xSx9udbx/+la1CrVauXWitTwf2X3PbmDpx/STDwMqGSxaZICSkzLouDuubGqS3iqriIKWBojINceJSuAHSRPvNOeg21wjbSJkNe89K4uJRJSumkybqAaPvhq5B4rrhXEkAqEFOeZYyEWBbXlEqGWRIymjCqSS29HaW1MibppLy6e5LctN5jfIcdR9w4kruO7Jwor5cJ7QtLweaMy7JYSdGJKYLEwtWWZmsO03di5Q8DeRhlIesH6HsJA3oLuXT/bBJuck4l8eYswYubHJyEYxZvBeiyA7wQ4U0jEZcNOZtCq6KWj+czMNUFT0MgdaFpRpWBSl8z1mCcKcUAHbbzhRd+ub0Jntk5cqaWOI5Dz2a9ASRmtoTAicwpRkKKhfcprscyCwdSHpL0Hx/Gnr7zpeF8aZtqRFTh85dnSUw871mWwPHwzOm4l4EUAjElXnaS6DmcJp53B5Z55vH5kWmaeN6d+OOfPtH1Pdube6zz7HYHQk4cTkf+/POfJZkw9LjO1YXBQFlVhYfnrMTytje3OO+L8kopG8sUOovEyKx10unQWGl/Ufin14GR1sJUgFKAyzlfxDJTSjVuqT3bW+BR5kLL13x6euLz588oAX0YhpoZn6aJr1+/klKqCZ4Y4wU5XYWY9bWbm5taOaQk+O++++7cqtnaqqqkdfKtMnxK6aK/u8ZnV6tVDS1I472z8vzHjx/Z7/c1cfWWyy6LdCmZNPIsjHf0vnTxdEXrM0dSEmJ5SpKHjdPCHI8Y63G9VOpY32FtL1lwK55GtiPZdNJQzHtSith5j48L23XH/dbhbOTrTjjKmzFzf2PovWczSLuYOQj393Q8ctjvsMYwDp1YV50hJS/T1mZJGi1HwjKzROGupgy+M7hexmrMYJIs4CCllJr9TSWc1XmHd5poc2Qy0xKJMePM61CSMRZnPd24YvX+O6zv2L97IHz+SDoeyU+nIh4imW+XEr4cawAwGftyxOdHlgj+/VdimllW74ibFf1gCTkAiXGzpgv3dM87lpsBZktIARsyznkGW+ZhljDLYiXOGkxiRlSRlk1HNAPRZKJN9bxMli6kqoqVpGcjucRUTcnToCHu0vW0StMlbSMin01k5uLRTL0hZMi3G/zDjeh+7vdwpUr3NniWfihWM77DyLBakXLiMM9CHiYTslQgaXwhF93NlIRFrxN+LKV/Dw8PAIQgddj7/YHd4cA0zXz58pV5mti/PHI8PDeWTWZ/isxL4niceNkfWJaF5+c98zKzOx4xj3Kczc2uAL7QmeYg3EZjzl32XNfhVysMBp+KV1NW8L7vyX6k66F0j6vGTl3IMgUUZCL0fS+2jHdvZgDfim0qQKirClQeZJtFV+4jnOv35f6F6k7v9/vqLqvLrUT7aZrq59uyyJYX2lKQWuk8VZbfbrcXlqVK0fV9X4F2GIaqOdq2aVVrc7PZ0HVdVdDXa9Ey0JYP+3Ztu2l+m2Jo2pqgrI8p2YtmuyYjSjlxxrqMJ2AtdKYX0Q+jTdYs2Y9k14NzZO+xKWDyjLWZobOsesu8gDOJZBK9z6x6w2rw3G6Gwk4oAr15Zj6Kddp5tWaBLIr2eo0hZmIKIgQUJUbpfCeLuz0rNsVU1IqiEudTHbPWnHURXDF6YpJSVZvtOXNSp7cImzvf06035BjYr1ek9QhxIZb75nOpHEpZfgpYGCBOs9B8+oE0HYidxZlE6C3emVry2vU93WqFGQfC6LEmkTvRJBAdDAGyrjw0vbcLYhkm4zCDI/qO4MF4U5+rXKgIkeSYBTyToKiRdrrF6smUnnPU4oGcsZECoKnoESRJkWVD9JaEIa963GoUEaM3chqvwHMYBr7/8QcMRpTcvWfopewxpUS3EnFQv+pZ3Wwk414m13Z7w2azZhyH6m6IVdJJB8xxJTGFaRYi8jRLxc40s0TJZmZzpmbYMhhGMq4D53tcPxDCgvGOaZ6Y5onTPBFjZl4WUs6sR2kbuuoHHtY3YuU4kbwynccOPdZYeuOKSyV1wF3fcXd/j/Neqky0BC4VVeqSYJJkmrhA0lbC09nrCX92bd8CUDgnSqo6VOlLdHNzw9/93d8xzzN3d3e19lwBUC29ltPZkuJ1fzqpttst7969qxZmW86nRPgQAu/evbuIj3rvq5KTMh9CCBwOB+Z5roLLDw8PF0LNGgOdpqkee7PZcH9/z83NTQVHBXJdCI7HIznnSvRvwTMa0TQI1hCKC5YRYrvLGmrQMh15niIi4zDGkbMTCbMcycuMS6KvkGwGY0negg0ka4W7mALMe3JcCMtEjjOWyNhbOm9Yj57N6Ok7g3dF2d07nIMw9CyroXgqoXTUFO/GOrGcU4a5hBRiSiyL1DWOw4jvBjrvRGfWlMz6WTSpji2al85jTdDFWvHeuRqWNXDhHMN6iwXWP/yKfDrByzOmH2FZsLsjzAHmhXxaSqigpFK8gGROC/3XR8LpKHP3+ZnZeU5dj82Z1XTEh4CLi3h2NmOMEPi1IqkY/vJ38Sq8TWAT2Rmsz0SfCZ0j9MV9dp5c9ACitaJ8n6QKyC4zpoTlchQ705ZktEQXc/mcxE2XRTy1zkjRRTYGFzMhZYbv3tPdbEkFi/4ieK63G75/+FCsn77SZYa+I6bEzeGFaZn5fv6B0zKVAaLcxK62XZhOR0KKWO/ph5FxXLPdbAkx8uXxK4fjxP5w5GUn7vo0B+kjjWksCpEbsL0jZUvKmdskE35cb5imiU9fPnM4TeQcOZ0mnAtshxWbvud2veY3799LiwtriMaQnCN3UpWx7gdp/6qUoK5js73BOicx1UlKOKd5IRpJXMWsNRuSvV1tNvI8lok8XwqmtlbgtQuvlqeChLrxatnd3t5eWGDqdit4KvdT3d9rC07FjYdh4OHhgV/96lfs9/uaMdcKn2VZ+Pz5M6fTiR9//LFWO6kVen9/T9/3fPnypQL08/MzAIeDeAF///d/z3fffQecqU9fvnzh8+fP/PDDD/yn//SfePfuHd999x13d3f1fNVq1j71Ly8vWGulC0FLuMcQbUewEJxlQSyDWLIhBtVtTWCkeWHnfInRKzPZEIsgb4gZa6VO2xVWd/KRbLuq7mNywIUdJgWW054YJiyR7UqqVG43ntuNL2phYhl6LyBt0oDJG8KysHt+JoSFYejpfAcYconnnUIgE+oYM9azuX1gHNZ0XrohkBN5ORFjoLboyCKWop0UKnhGSYNYAOUmXokB6RLjfcfm9oEwrkh//x9wmzXx61fC3T35NJE+P8LhJH8fT8LbDHNxcwNdCpg4kf78E945pi9fyP3AZCw7DM47+rsbue7lRO8y3oF1CRMjta2JshaMwTlJ63uLtPt2Bt8lYp+JvSWOPdl3xPWG5DvS2BNHMYQ668RiPp1w80zMmSVHsJZuc4Pt+lppREzYOZBj4rg/kA9HTAlPZmOY5kgIifVvf8P47h05CI79RfDsvGd7K7GvzndY6/BeKntiSmRvGMLCEhfmUqOu1orKxk3TRKa0AXZFYMCJlqEzhq7vxRJdAqsl0oeIsyIIMp8MYbbVepAavB6QJmwpC3gaa8VtPYpYha4qWnHiyw0duq4oxVuCMcJf7cWyEcrUGTyd9yKtZ6WPdJcyNkoWNlhHP4zVMuqGQVgChTIRcmSZK2+iDuhvUZMuBrQ5y7FdJ4ta4G1FINqqKN2HCoSklGrLDK3iUt6mtgpWZXi1fruuq+emPea1ukjjqPM8V9DX6iN9XeO42ue91SzVn7am/S1q0vV9OYOnyDUGxOqMSego2j/VVlgpykRAzBd9Li9U6UqWBqPdLY0mBTMRCtcvQoiQZFGPURJRzooYiS1y8Tmjoj3nlKmRjq/ZSQ1+TpZzJUyuQ8QWa0ti7vZMhs9nhoGGLLLut1hQOZerfiOxKJGNt5iQ7ZiTsIdLPX69ob+5k95ppyN5Enpe7o9wPEHXkWMUAyElSAvEUPoRSY+h3hZXN2eG4ha7ECRBlFIV9VMHweiF1id2Dv/JJZSbS4Ii8ZeDyPDlJUK25E7CephMsueETzZaumlLyE5CMfU+OqGiERNp6UghYJyDvpMkpE3YmLHjgOt6HEsp+73cXoHn9vaW/+E//ScRzS2vWXsORsccKzleBVyVZ6ZfeHl54V//+K/EEFivVtiuw3UD3bCiN/Djr35drBihXGgiJqXE89Mn9i+PBTDE9by9+45xta1SffM88+c//8x+v2f4X/9Xnnci7DuHBVKmt45N13E7DLxbrRn6nth3JO9wqwG/3ZTMuQwx60pNtCk1zEYSC32/koeQZGLd3d8TQyitOUpZXLn2508/83TcXyQ527ptTaJc1623cnTXNCYlP7fWpAoYb7fbalHq/pTrZwuj4bvvvmMcR969e8fNzU1NRrUWakvGt9ZWjdAQAi8vL/zzP/+zdDXd7zmdTjWRpBZsSonn5+cqjffx40dOp1N123e7HT/99FNVxNcwwDXroLXIr2OeIcHLZJiBOSSWIM/MdQocJXyBBP7JsCwyU2xJflhr6DshovssQsM2Z1KZzdlK47EQ5V4SA/kwkcPMbr+wOySwjqHfyLNPnukkgsSLKyRqmyRZlSW2bqxltdkSo+hWhhJOyaV/vDew9p7OGnw3Ag5nsoAUuShsFGXREj/uOnFPU5AMiStpfF0UNGssAPTtzThHN65w3cDNb/4vrD58x3zYc/r1b4jzzOnLF+LxSNofSC8v5BAIxz3EgAkLNi64DNuyOm3wJCxLjKKeljMsM2Y50p1O9KkozntXWhQX9aYKkECytWwyJ+lJukwnljCzHCaWfATjoDuB8yzrgXk9YL0naoJ1nrEhEA2EklicfcBGW1x+Kd5JJQl8co6pl8S4G3qMtcLjtp7u/h3r2zuY5pLj+Avg2fU9D+/fVbdR6RCmBiaAkpWq/7VCHiVQ/PLywjyJtJmxjeVpLeuNZq7PbAKhWWTGwfE8FIm2mLDO8eG7H9ne3FfwnKYJaw0vux1/+OMfhINoDEuQyLDD0FlLbx2j7xh8R+p7cufpVmv67facGc9SzocVSyUW6oO0MD5bNDlDP/YlGC70inbhOD4/XtzHaxBskyHt32qFVZLz1ffVVW/FNGoirvQcaquDNBSw2Wz4/vvvK2Bq18pW/k6P3UrAaVJJFeyfn5+rar1WIrWWMnDR5E3VmnTB0BJP59zF96/J+u01X28pS/gN5HcIUjhsCzFbZem0Rlxc2GJdFgvGZXBeqnOUnpSNWHBKe8JacjRFA1bYHnkJLEuRkfOGYewKV9MSQya5fLao1MRFlIss1PhtyHNtV4Nq5JZxZKwTMZEKHGJpkVK1nY0R0RDvhVMqd15t7zqJqq2qzJxvbcaUWKDN9PYGv15hVivi0GHnmaXvyccjebcjrUZyWEj7kRwCLszksGBTposJk2CIEiIIYWFYDNLnbCaGBZcSDsktGGuL4GfRFDDyfI3eulTcA30GMRCyIYTEHAIGh3Vyz2qHzL4jIwZQnhesFk0U5WMbEjjN9uZilRYZQWuYnehheFfYGP2A9T1uHPH9iE/8dZanMUayfc7XrJ48Gn1M50C1vt72sCZDP6x4ePjAEorGJZlhtca5TuqOKTqPVgDUcCZLW++xzmNsBhNFPd45yY5moRf4zrO9ucF1ntu7e25vbjgcj8yniZhCSVhMHNyB5+dnhr7HpDWm71isIfZeEg4leJxMqc+1DlcI1WCLAIItijoGazxKR1bXSPfhu16H7XnSNxZeq1SkMUdN4CiwaZImhMBut0MbuWkzt7Y/kVbxaCy0lZLTLLcC52azqRan/iiQqfu8LAtfv36tlCEFUK2B1x89bluHvtvt+PTpEymlSqDX41hrax/23/72txKcL+GGcRx5eHjgcDhUC/YtNzRlmIJ4IqkuuKZ4RLbqvdcsa1YAMeW52ZK9LlzQmIjpnKQwWYo/rPXFenQkInMo5HYMxnts1+H7rrqq0lRMDqZN4M7uuQHjsN2AdRnnO7o4FoL7RC5E9xCW0vddJmg3CJOj6x1jr4uKWJvCNy0LbaPrqShki8lpyv/sL6Fn+0EniTc/wIAhxYhxA3GeSTcH4u2eFBbCfkdaxAKNxyMhRk7LBCnjbInf54RJAZMS/XQUkD2esIcjZl5Iz8+YZZYE1XQihUQ6LVQ5+SSsg5yEyL6PgYnMPhqeg8Fbz13v6JwnnjLEhTQOxL6X3mRDL4ZQloozYx3Odhg8WCctP8iEQpU8TDOnmOid59b3dF3P5v49680NN+8+MK7WhHQpeqPb2yT5UtKmI1ViLFoWla4yeJc+gjEwjGveffi+DBQpixxXKwnaGoQKVYQZMGdaU84J6zuc76RETEnpzguAgpST2Y6buztWmzUP7x64v7/HOcfL1yfikgnzwul4ZI80ouv7ni5H3GqkM5nghQoSS12wJAkyzvesN74od5eElXVY3xfirK0rkBpI2gTPd8M1dl4kjFRCrLXItMxRW210XVd5l9qbaLfb8fj4WGOWOeeqiJRzZhzHCytW96/7Wq/XlSLUVhXtdrtKZdKKplZ+TquUFDzb8IN2MhWmgeP5+bkmrl5eXmr8U8MW4zhWXqp26ux74Wi+e/eu3g8F4OuBmhJMi6goSRMvJMuuYr3FNc8pElMsK7srHpNYE5gymZIhlB7fwkYzOG9wRgwGExOYQMZyWhLLHIlFu8B2nbR4cQ5MrKBXjd+znQhF5Nh3/vwZI4r47EvIY1oI8yKVLwas84ze0g+ernP0vVhOsYSNaoIxZ4HtLNxq7VhprcRWTZ2L5tWYfDXXyRgr2qPO94zjhpwy/eZe7udpIp6OpBCYdztiWNh9/cr0/MQSFo7HPYlEN3S43tFbw8pJuKQ7iQudp5l0nGCeyV8eyfNMfnqBlx1pWli+HqTp5BQkpmqEkhWI7JaJY1z4EuFjhNF1dKZjnTMpSPeGFDYs2y3ZWsKwIq1GoTEFUdfq3IC1nmwdyQt4ztkJh9wY9jGxyYZNN9KPI9sP3/Pw7gN3D+8Y11vm0tr8ensFnimLxNy8BHFfNJtXEUOrDfRVDYCbCqAxaaRG+7zIih+TVkw0yROKwVpinJm3f+TwuQ5O6ywuSxsP7z2+uJ46VhJZeml3Htd39OOIX69xQ4/1rrg4piQOSqdM32FcqZTA1t40BqlEsa8C+K8cp1fbNUXpLfDUrLV+XsHzdDrVDpqaDIKzIhKIW/hWpc+3xIr15zrGqlnyVvj4W/Jzuk89noJsG+NtY7Zt0kktTz0ntUKVX9rSqJq7WI6bqouu7pf+mPY6QWqtc9tH6RweuMxAl+tJSZISSarOpKY7C4/ZiMXnvbh23lmkIt3Up581dlcERs5bATMjv61Nxe2XcmbrHAlbFJ4kVBCcqM8nrYjSlTqnUob4jUo1843f39xynbZtgkmb32VjMF3C5kRyYkylIFV+S4ik+cQyT4QYmGKCubQBT8KddHOoPYJYIoR0rujCioVvEqG0xAlZWiy7nOhLoxNpaGkJ1jDZok/gHcZZfIy4UkIrTTONZOP7gRxFd8MYK6I9viN3luxdCeuEknR0ZGNxXc/m5pbNas3m5ob1dku/Gisv9q0YyCvwXJbA48uBGV+tTrHuzy5BGQvnOA8KJvIIxHVWsCgu6xJwU1HBKfWO+uiN0WZbwhmV7nYqF1YyoJSC/fKaLWA5jCOb1ZplmkuViXx2Aeh7Vg8PrNZr7n/8gdXtDcEg1QsZQikJNb7DeFFT6voRY23R/JT2pbZ0R/ROml3VQVtAn5xFuvB6aDbAqVajAsnLywsfP36k73seHx9rDFGFOr58+cI8zzw+PvL8/Ezf9zw/P9cqJbXQttttBb/Wym2rkdpulAogbZxSBT0eHx+r695apXCuSNJ96jHbEk61itXKVtDd7XbknHl5eSlFC6aC5Gq14vb2lpubmxq/vSbKKw0npYj1SGzSZKKJxV0urrIVa9SUEIvS3ZTyJkBE2VdTF54gz4V2F6QZWAoLS0wsMdH1HWMvIjebUTq/SiFL6c+UpBYtZ1vmQQn3NIuVteLNOGMZjbjGKUviZpoD015c+QM77OnEMPbEOFZOr7G2ZPy1BY3OOrE6TRGFNkbHJPDNJb3e2aqorpE3W12qskiNI3kcZKzf3pJTptveMux2PD595eVw5BASTy8HDsvM/njk8emJFHNVjfdWchA2Jfy8YGLCB/DJCc/VdiRrOYY98+nIrUl8ZxK9gVvr6I1nWnm+rjui89Cv6KxlfDkxHGeOc+RzNMzZcdxsOb27J82RcArCilivZcH2ohUYY2TZHwWs7QAusLl9z7//H/4jdze3PHz3PZubW5x1olnxDa3eV+AZc2ZeAv6q1aZOIqtB6SamcrZubAVHVYCJSepwBUTP9cbNngsQFxdaQbOGC7h4TVXBbQlYuTK4vHPntVNjUN7hxoFutWJYrxg3G+YUCTGIKEROZJOxvsd2Y+mYKW1yc8xk7VKThQRtM2VAyMCrGFoA/ZtDNJ9FQNo69NPpVC0zfU/Bc7fbVS6kAlIrqAHUMkq9/21NeSuy8dam56EWZ0tL0p82mdTu8zrBo/tp2QH6fquQ1bYw1vPSTH+rTar7ur6HOZ9tzfN/NeR3tqBMqZsujAqJBRZXOiOKSjpONIGTIjmGEqpqWA+ZQskpVmcZcynbqmJu9Oln9VVyY/21FosAvS30PVfocTaUbgdJ7p9JGecMoROKnS0tR6jH0OtVy1FBurlfvzgi6y70w5qjOb/Wxp71d9dJTiNGlpxx80xynsU4DjHzPAeeDhM/Pe0JMQGOjCRf+86LKx8jNie6mPFRQF5pZfucmVLkSMKbxMoYVqajN5bkOpa+JziHSPIbvJEeSjGX5BuG5Dpi3xNzZFlkvsSuw3Wd9H73RcXKWKErWYe1nr4fubm94+buTrpIbDa1yOBboePX4BkTh9NMdtPVwiUj1OkgPXvpjQWp4BmJYSHnRIqzxE5KKVWbqKl7NUYoF2QOhyPH05l8r4R1Y/uz60Ypq0NW7s3NDdM8SxWAMfhhZLy9YXN/z90PP7Ber3HrNcFaQs6E8rBM12GxGNdjO6mKyqZwRk2q5Q9n66bSlC9uzbm91OutpeW0P8fjkS9fvlxk0VsrVbtQatKmzbSrFagZda1t1/cVRBX4tG86vI7DTtPEfr+vMU4FPAVPPVb7W/ejVqImoBQ8W76qfk5Kap/585//zLIsrFYrVLQ5ZykQ2G63ld50scCW555SJIRMyrZ4HwKOXRGxEWdQBqYMtQK0tZVMGXOlNQttWCqlkuUOmBSxWX5cmcidyXQkbJZOCdZQ4vAC0griuVhymLOVq4t+TqkxOmRB1u6xWdtKFHWgkBBRGpAKqnJ1Z0m/wvqoxoepEbRUw2JXA/UvbNc439j+F4bJMIhIEMbw3/3233E4nbj//IWn3Y6PwzMhWw7TzB8fH3k5naTbaJL7740YLeZ5h9kdRIxkjpAyszGE9ch9Cuziwo0x3LierZMS8c3Nms5adq4DLHFxxNRzWq05uZ7JeI5zYL8/EZciM2lE3L3LRcglWOKycNzviUvgdr3h5t17fvXjD9y/e892u6Ub+nqt9fcb0/t1zDMlTtMMbpaEjgy/+r6qXCmA0j4fUwZSaTNMTqS0QBbGfogCM2o9ni1WinWQORxPnAp4ggRqT6cTpkhU6cqrvV5sEZw4HA4ymI3BjwPDdsvq/o7b7z+wWq0JJWEQkoAniD6nNSJubFxfB0wGsimB67JKqCCFDqXG3qix3V/arsHzdDrx+PhY3VnNYrcxyDZWqu66Ch+rpfbhw4eaLU8p1aqiEEKt4FGLTp9vG5tU8FRBjzZO2crGabKipSm1YQl15VsKlF6PWqbPz881KXRzcyOVX+V7WgrqnKuK9pf3r7T1jed2wXZxMiGykUZ9UIy7sxUWo5QEQgue54X7fAAhYJOiKCLlKPE7Ep5EZ+S3ydpmpsQEjYXS3yin877JVHV5vd+hkMY776vx4azDqoBHLkpr2RCigKdYpOr2azhA23Ccr1UtR3nGhceY/tKo/IZJ9cbLGsAznD2eruvocUzzzNqteOyf6P3Iy5J4POw5fP7Mn48HDnNgNwUMkpwzQPr6RHp6xmbok8xlVh15NfAYLLs58Q7D/+AHsCI+vtrc4I1lb5zM4ZXDpJ7TOHLyPbP1HOfI8TCxxMwcRKAoLgsd4I2EENI8S2VRjGzfveM3P/7Id99/x939A6v16qz1qaHJt732txvA6SqjiYUmlFxh4+273WYbm8GpslG5cPF01Yfz76SxrcLR0yB8Lp0MQ6wWiFgWKrFvpFppGBnGgXkeGVcrVpsN/TjWwHdIEpeMGbAepSCZUjGSFTnVlcMUyhLnlUIHdzOcdLX/a1d4nUhaG67UozZOqIDTgtM1kAEXFUctqGliRrU1taJIP9dmz1vOp9Kb9D21WlvBkHr1jdt9Leihrv114ketSu39ruIkaiUrI+BVAzhTrhsFENOAsyYgo/Q/N7Zmtm0Bllwen7q4bQhALMWyqGnCSDmW5TMpZ3FDTcKXihbjTc3i60GyhnKa53b9Y7B1fAnXUPqY55I0wXalu6UnIjJ5AqJFhk1EReu9Pd/nYp3nLBVRKRHTN8DxetNIQ1l9xPOqdT8XH2s3ay3d0IGBzXZNSJGjiXxYDnSD58fne3DwuDuR8kFCeWURzCDN8tI5pIWx4DqWnDk4z5DhKUW+poUpRPycMM5w7Cyzs9D30rSu73nxjsVZjikzLYGQMkvh+falkk4S1JlcFjFjHOvNmrv7OzabDdbZep2aFP+lO/ia50lRabGXMTOFQ5dTA5UUa62ApsK00UNbUdIGRFHGUYP76k6VagsV4ViWTFw0/pmwNjNNC9jpwm3X+IHxHbf3Dywxcv/uPa7ref/993z344/c3N2TvXSbPi2RKSSM88VFt+B66R8DZxdHRo4kHEobB71anaivx93Znb94r0kY6GBvY4zqnqrLrd+R88mv9qUueUqiwKQuvQKcllSqmrtSg+rD9tJPCqh9i/Qn51wpTeM4vuqMqeelZaFqPetCoO63XkfLbdVF+OvXrxgj9LHdbsc4jvzwww+1jPT7779nv9/z6dOnC+vT2kLfyRljzt0iQQQz5iCtf6UHj9yHHksuQhy2ARrKI07lD7XYUgiYbElxIZcftUCXJRCzpevB9BGXDb23Uque9flraKFk6tO5r9NlLDjjCo0qZmlwEU0kGWlnYfwK4zzBOmK22ATpFHEmMHhL7yXz3/XdRVw3pViTtPJcIrMDnPKP39oMSup//RHT/P/tzXnHZrsR8Oscdw+33O7v2Dxs2J2OjJueT89P/OOfPvH//P2fOM4zj7sXlhhkXnlPDokQZ0EL22G7FSfj+ZQNp5j4x9PEFE+sdpZNP7AMPR8fNsy+Y7iVTpvJOkJXkk4xMB+kzU4qc8bNUlrOspCXGW8MG+8YO88PP3zgP/zD34sgi/cX1/yXlp43eJ5v3uLyW/2DM5ie7dCzTdq6saYGT0y17mqYXUVKuSRAq/hwTSA1lo26/Ocq/ybp0Hf0Q6mbH0e6vieXFV4KTgTinBFrk0JBaEKw1Ms6n/1lfPM6AaOmzRubxghzzheJl7fq1ttEzOXuz69du/46OfUeaOxTwVnBTe+fciv12K21qFamAuP1pp9tZfQ0HNCyCc4xudcWqMZYnXOVxzpNE+M4Vu6nJs/eupc2n7PYMn7O1l4uteoJwEh83WhBu15O41nUuHvJkmiMPaes/rfcF0QMJkbJTISYpbijvHt2ys7Hyc2z0vvQPNH2qijckRprl3CAF0Mky70MRj7lTSoFOK/HbJ0vqRGfMWqp/tLWnI8uMr/w6fZapKBGWARD0VjY5MBtWOO85f3tDZjM4+7IdhyxxrA/7klRrPVolMqYkMovwY5YfjpgnxIvMeBC5GaJGJdYMkzGEJyT/lFWetBnA1OS9zEiquyQsW6NIYcgilHe0fm+Fmqs1ys63xWB7NdP6Vvb69bD+VKp+uJmUfOb53hnPr+WMyIVlVJtTFUIWAKdpb1qBdbaZEWB9xxlyghlySTLkkwRxzZnt9kAJjMvkek0kZbIzTDSpcz9zS13t/f0w4olGUkyGOGGYTwR6Vcj2f9vAeclgGiI4XozZQfXgGOt5d27dwzDUBrSiRLR+/cSlG5r2tvss97Ttg2wApdmsZWcnlLi559/xhhTq3ra2nkVF1Ya0zAMNa7YtsPYbDYAZ+X/8tN+9+PHj9Vy1HNVV14HYWt5qkWr1q6u6m3IIoRQKVk3N9IMsC0Vbe+xMWd9pPOtknFjTKHrlN7tZIqlJ62nvXdnIwt9TwDS6KKVRC3eFP6m1EH3kCzHAMcl0i+B5AJdAOMTrjuPXAO1ek6DZLWPfHl2rUQjGKLJonnhDNHGQncTVz3MmSUFnMlsfEm0GGntkYnYuJQMvCTLYoyERehcMaazi/xqxP6ft7X7Vu/HFN3caVkw1vFyPHC/uuP9+o6nlxf+13/+J552L3xZAl/3e1JaWOIMCeLuBbMs0nZjWcgp8rv5yHNa+A++54NfYZaMWZ8gJU5jz9yXBbwkdENUBXyDR0D6tAQWY/GIQv44DPy7v/stD7e3/PDd96zGFdY2bJ2/cnsz5qkAmq+WNyWHmMYcy/V1jWWWJlWlOVUtuzJZUv/mvDcZeLZkReX7Qlp1pY5drJaQwCZzbhMLtSB2CZFllhu+6no8sF2t2ay3GNdJ+1UgU2RXrKgkJUXNpqlTvXlvgOS3tnPs7LWbfXt7y3a75Xg8VvB4eHhgs9lUwIGzFaj7U9C6Jp1rUknV21NKPD4+XlT2tHFMtTqVHjQMA8fjsQqLjONYE1Aac9Ss93a7vcj2H4/HugBojErjqHrebcJIGQJqUbZCzlogEGPk+fm58lJbpaXrTTjEkpW+eB0j8mtZwFO9HxXhwFB0PanB6RCEbaDPWb5lydkWRa6St7cenGGaAs+nyJASfggMybBayxj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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    },
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "horse truck  deer   car\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# 输出图像的函数\n",
    "def imgshow(img):\n",
    "    img = img/2+0.5  # unnormalize\n",
    "    npimg = img.numpy()\n",
    "    plt.imshow(np.transpose(npimg, (1,2,0)))\n",
    "    plt.show()\n",
    "\n",
    "# 随机获取训练图片\n",
    "dataIter = iter(trainloader)\n",
    "images, labels = dataIter.next()\n",
    "\n",
    "# 显示图片\n",
    "imgshow(torchvision.utils.make_grid(images))\n",
    "# 打印图片标签\n",
    "print(' '.join('%5s'%classes[labels[j]] for j in range(4)))"
   ]
  },
  {
   "source": [
    "# 2.定义一个卷积神经网络\n",
    "将之前神经网络章节定义的神经网络拿过来，并将其修改成输入为3通道图像(替代原来定义的单通道图像）。"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "\n",
    "class Net(nn.Module):\n",
    "    def __init__(self):\n",
    "        super(Net, self).__init__()\n",
    "        self.conv1 = nn.Conv2d(3,6,5)\n",
    "        self.pool = nn.MaxPool2d(2,2)\n",
    "        self.conv2 = nn.Conv2d(6,16,5)\n",
    "        self.fc1 = nn.Linear(16*5*5, 120)\n",
    "        self.fc2 = nn.Linear(120, 84)\n",
    "        self.fc3 = nn.Linear(84, 10)\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = self.pool(F.relu(self.conv1(x)))\n",
    "        x = self.pool(F.relu(self.conv2(x)))\n",
    "        x = x.view(-1, 16*5*5)\n",
    "        x = F.relu(self.fc1(x))\n",
    "        x = F.relu(self.fc2(x))\n",
    "        x = self.fc3(x)\n",
    "        return x\n",
    "\n",
    "net = Net()"
   ]
  },
  {
   "source": [
    "# 3.定义损失函数和优化器\n",
    "我们使用多分类的交叉熵损失函数和随机梯度下降优化器(使用 momentum ）。"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch.optim as optim\n",
    "\n",
    "criterion = nn.CrossEntropyLoss()\n",
    "optimizer = optim.SGD(net.parameters(), lr=0.001, momentum=0.9)"
   ]
  },
  {
   "source": [
    "# 4.训练网络\n",
    "事情开始变得有趣了。我们只需要遍历我们的数据迭代器，并将输入“喂”给网络和优化函数。"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "[1,  2000] loss 2.218\n",
      "[1,  4000] loss 1.883\n",
      "[1,  6000] loss 1.699\n",
      "[1,  8000] loss 1.592\n",
      "[1, 10000] loss 1.523\n",
      "[1, 12000] loss 1.471\n",
      "[2,  2000] loss 1.378\n",
      "[2,  4000] loss 1.363\n",
      "[2,  6000] loss 1.329\n",
      "[2,  8000] loss 1.327\n",
      "[2, 10000] loss 1.285\n",
      "[2, 12000] loss 1.259\n",
      "train finished\n"
     ]
    }
   ],
   "source": [
    "for epoch in range(2):\n",
    "    running_loss = 0.0\n",
    "    for i, data in enumerate(trainloader, 0):\n",
    "        inputs, labels = data # get inputs\n",
    "\n",
    "        optimizer.zero_grad()\n",
    "\n",
    "        # forward + backward + optimize\n",
    "        outputs = net(inputs)\n",
    "        loss = criterion(outputs, labels)\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "\n",
    "        # print statistics\n",
    "        running_loss += loss.item()\n",
    "        if i%2000==1999:\n",
    "            print('[%d, %5d] loss %.3f'%(epoch+1, i+1, running_loss/2000))\n",
    "            running_loss=0.0\n",
    "\n",
    "print('train finished')\n",
    "\n",
    "model_path = './cifar_net.pth'\n",
    "torch.save(net.state_dict(), model_path) # 保存已训练得到的模型"
   ]
  },
  {
   "source": [
    "看这里熟悉更多PyTorch [保存模型](https://pytorch.org/docs/stable/notes/serialization.html)的细节\n",
    "# 5.使用测试数据测试网络\n",
    "我们已经在训练集上训练了2遍网络。但是我们需要检查网络是否学到了一些东西。\n",
    "\n",
    "我们将通过预测神经网络输出的标签来检查这个问题，并和正确样本进行 ( `ground-truth`）对比。如果预测是正确的，我们将样本添加到正确预测的列表中。\n",
    "\n",
    "ok，第一步。让我们展示测试集中的图像来熟悉一下。"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n<svg height=\"121.003431pt\" version=\"1.1\" viewBox=\"0 0 368.925 121.003431\" width=\"368.925pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n <metadata>\n  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n   <cc:Work>\n    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n    <dc:date>2021-06-16T20:47:07.241406</dc:date>\n    <dc:format>image/svg+xml</dc:format>\n    <dc:creator>\n     <cc:Agent>\n      <dc:title>Matplotlib v3.4.2, https://matplotlib.org/</dc:title>\n     </cc:Agent>\n    </dc:creator>\n   </cc:Work>\n  </rdf:RDF>\n </metadata>\n <defs>\n  <style 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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    },
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "GroundTruth:    cat  ship  ship plane\n"
     ]
    }
   ],
   "source": [
    "dataIter = iter(testloader)\n",
    "images, labels = dataIter.next()\n",
    "\n",
    "# 输出图片\n",
    "imgshow(torchvision.utils.make_grid(images))\n",
    "print('GroundTruth: ', ' '.join('%5s'%classes[labels[j]] for j in range(4)))"
   ]
  },
  {
   "source": [
    "下一步，让我们加载保存的模型（注意：在这里保存和加载模型不是必要的，我们只是为了解释如何去做这件事）"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Predicted :    cat  ship  ship plane\n"
     ]
    }
   ],
   "source": [
    "net = Net()\n",
    "net.load_state_dict(torch.load(model_path))  # 加载模型\n",
    "\n",
    "outputs = net(images)                       # 输出是10个类别的量值。一个类的值越高，网络就越认为这个图像属于这个特定的类。\n",
    "_, predicted = torch.max(outputs, 1)        # 最高量值的下标/索引\n",
    "\n",
    "print('Predicted : ', ' '.join('%5s'%classes[labels[j]] for j in range(4)))"
   ]
  },
  {
   "source": [
    "结果还不错。\n",
    "\n",
    "让我们看看网络在整个数据集上表现的怎么样。"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "torch.Size([4])\n",
      "torch.Size([4])\n",
      "Accuracy of network on 10000 test images : 56 %\n"
     ]
    }
   ],
   "source": [
    "correct = 0 \n",
    "total = 0\n",
    "\n",
    "ifOutput=False\n",
    "\n",
    "with torch.no_grad():   # 此作用域内，不计算梯度\n",
    "    for data in testloader:\n",
    "        images, labels = data\n",
    "        outputs = net(images)\n",
    "        _, predicted = torch.max(outputs.data, 1)\n",
    "        total += labels.size(0)\n",
    "        if not ifOutput:\n",
    "            print(labels.size())\n",
    "            print(predicted.size())\n",
    "            ifOutput = True\n",
    "        correct += (predicted ==labels).sum().item()\n",
    "\n",
    "print('Accuracy of network on 10000 test images : %d %%' % (100.0*correct/total))"
   ]
  },
  {
   "source": [
    "这比随机选取(即从10个类中随机选择一个类，正确率是10%）要好很多。看来网络确实学到了一些东西。\n",
    "\n",
    "那么哪些是表现好的类呢？哪些是表现的差的类呢？\n",
    "\n",
    "# 查看每个类别的正确率"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Accuracy of plane : 56 %\nAccuracy of   car : 76 %\nAccuracy of  bird : 42 %\nAccuracy of   cat : 40 %\nAccuracy of  deer : 43 %\nAccuracy of   dog : 51 %\nAccuracy of  frog : 66 %\nAccuracy of horse : 64 %\nAccuracy of  ship : 66 %\nAccuracy of truck : 52 %\n"
     ]
    }
   ],
   "source": [
    "class_correct = list(0. for i in range(10))\n",
    "class_total = list(0. for i in range(10))\n",
    "\n",
    "with torch.no_grad():\n",
    "    for data in testloader:\n",
    "        images, labels = data\n",
    "        outputs = net(images)\n",
    "        _, predicted = torch.max(outputs, 1)\n",
    "        c = (predicted==labels).squeeze()\n",
    "        for i in range(4):\n",
    "            label = labels[i]\n",
    "            class_correct[label] += c[i].item()\n",
    "            class_total[label]+=1\n",
    "\n",
    "for i in range(10):\n",
    "    print('Accuracy of %5s : %2d %%'%(classes[i], 100.0*class_correct[i]/class_total[i]))\n",
    "    "
   ]
  },
  {
   "source": [
    "# 在GPU上训练\n",
    "与将一个张量传递给 GPU 一样，可以这样将神经网络转移到 GPU 上。\n",
    "\n",
    "如果我们有 cuda 可用的话，让我们首先定义第一个设备为可见 cuda 设备："
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "cuda:0\n",
      "[1,  2000] loss 2.220\n",
      "[1,  4000] loss 1.856\n",
      "[1,  6000] loss 1.662\n",
      "[1,  8000] loss 1.559\n",
      "[1, 10000] loss 1.504\n",
      "[1, 12000] loss 1.473\n",
      "[2,  2000] loss 1.376\n",
      "[2,  4000] loss 1.370\n",
      "[2,  6000] loss 1.353\n",
      "[2,  8000] loss 1.303\n",
      "[2, 10000] loss 1.268\n",
      "[2, 12000] loss 1.291\n",
      "Accuracy of network on 10000 test images : 56 %\n"
     ]
    }
   ],
   "source": [
    "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
    "\n",
    "print(device)\n",
    "\n",
    "net_gpu = Net()\n",
    "net_gpu.to(device)          # 递归遍历所有模块，并将它们的参数和缓冲区转换为CUDA张量\n",
    "\n",
    "#inputs = inputs.to(device)      # 将输入和目标在每一步都送入GPU\n",
    "#labels = labels.to(device)      # 将输入和目标在每一步都送入GPU\n",
    "\n",
    "correct = 0 \n",
    "total = 0\n",
    "\n",
    "criterion_gpu = nn.CrossEntropyLoss()\n",
    "optimizer_gpu = optim.SGD(net_gpu.parameters(), lr=0.001, momentum=0.9)\n",
    "\n",
    "for epoch in range(2):\n",
    "    running_loss = 0.0\n",
    "    for i, data in enumerate(trainloader, 0):\n",
    "        inputs, labels = data # get inputs\n",
    "\n",
    "        inputs = inputs.to(device)\n",
    "        labels = labels.to(device)\n",
    "\n",
    "        optimizer_gpu.zero_grad()\n",
    "\n",
    "        # forward + backward + optimize\n",
    "        outputs = net_gpu(inputs)\n",
    "        loss = criterion_gpu(outputs, labels)\n",
    "        loss.backward()\n",
    "        optimizer_gpu.step()\n",
    "\n",
    "        # print statistics\n",
    "        running_loss += loss.item()\n",
    "        if i%2000==1999:\n",
    "            print('[%d, %5d] loss %.3f'%(epoch+1, i+1, running_loss/2000))\n",
    "            running_loss=0.0\n",
    "\n",
    "with torch.no_grad():   # 此作用域内，不计算梯度\n",
    "    for data in testloader:\n",
    "        images, labels = data\n",
    "        images = images.to(device)\n",
    "        labels = labels.to(device)\n",
    "        outputs = net_gpu(images)\n",
    "        _, predicted = torch.max(outputs.data, 1)\n",
    "        total += labels.size(0)\n",
    "        #print('predicted size : ', predicted.size())\n",
    "        #print('labels size    : ', labels.size())\n",
    "        correct += (predicted ==labels).sum().item()\n",
    "\n",
    "print('Accuracy of network on 10000 test images : %d %%' % (100.0*correct/total))\n"
   ]
  },
  {
   "source": [
    "为什么我们感受不到与CPU相比的巨大加速？因为我们的网络实在是太小了。\n",
    "\n",
    "尝试一下：加宽你的网络(注意第一个`nn.Conv2d`的第二个参数和第二个`nn.Conv2d`的第一个参数要相同），看看能获得多少加速。\n",
    "\n",
    "已实现的目标：\n",
    "\n",
    "在更高层次上理解 PyTorch 的 Tensor 库和神经网络\n",
    "训练一个小的神经网络做图片分类\n",
    "在多GPU上训练\n",
    "如果希望使用您所有GPU获得更大的加速，请查看[Optional: Data Parallelism](https://pytorch.org/tutorials/beginner/blitz/data_parallel_tutorial.html)。\n",
    "\n",
    "接下来要做什么？\n",
    "\n",
    "[Train neural nets to play video games](https://pytorch.org/tutorials/intermediate/reinforcement_q_learning.html    )\n",
    "\n",
    "[Train a state-of-the-art ResNet network on imagenet](https://github.com/pytorch/examples/tree/master/imagenet)\n",
    "\n",
    "[Train a face generator using Generative Adversarial Networks](https://github.com/pytorch/examples/tree/master/dcgan)\n",
    "\n",
    "[Train a word-level language model using Recurrent LSTM networks](https://github.com/pytorch/examples/tree/master/word_language_model)\n",
    "\n",
    "[More examples](https://github.com/pytorch/examples)\n",
    "\n",
    "[More tutorials](https://github.com/pytorch/tutorials)\n",
    "\n",
    "[Discuss PyTorch on the Forums](https://discuss.pytorch.org/)\n",
    "\n",
    "[Chat with other users on Slack](https://pytorch.slack.com/messages/beginner/)"
   ],
   "cell_type": "markdown",
   "metadata": {}
  }
 ]
}